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• The "how" over the "who": A machine learning approach to understanding clinical judgment in acute suicide risk assessment
  Background: Suicide is a pressing public health crisis in Bogotá, Colombia. Despite escalating rates, a gap exists in data-driven research using localized, real-world clinical data. This study aimed to train and interpret a machine learning model to predict ac…
  datacite Jaramillo-Gutiérrez, Juan Camilo 2026 置信度 0.66 Suicidio en BogotáMachine LearningPredicción de riesgo agudoMétodos de alta letalidadDatos epidemiológicos
• hypertopos
  hypertopos is a Python library that transforms relational data into a geometric space where structure, anomalies and change become directly observable — without training machine learning models. Every entity gets a coordinate derived from its typed relationshi…
  datacite Karol Kędzia 2026 置信度 0.66 geometric data analysisanomaly detectionunsupervised learningrelational datadrift detection
• Evaluating AI Tools for COPD Management: NLP-Based Identification of Exacerbations in Local EHRs
  In this study we evaluate the performance of classical machine learning models, and transformer?based models (BioClinicalBERT and large language models (LLMs) for the automatic identification of COPD exacerbations using unstructured clinical texts from Colombi…
  datacite Campos Lozano, Jonathan, Ruiz Rodriguez, Nini Yohana, Jaimes Fernandez, Diego Alejandro, Jaimes Fernandez, Diego Alejandro 等 2025 置信度 0.66 Chronic Obstructive Pulmonary Disease (COPD)Exacerbation DetectionBioClinicalBERTClinical RecordsNatural Language Processing
• Cone density estimation in AOSLO images using image processing and deep learning
  In ophthalmology, early detection of degenerative diseases in the eye is crucial, however, many times conventional clinical cameras do not allow quantification of retinal cell loss and, in addition, manual analysis of these images is inefficient and poorly aut…
  datacite Cerda Cortez, Nicolay Agustin 2026 置信度 0.66 AOSLODensidad de conosAprendizaje profundo livianoEstimación automatizadaDespliegue clínico
• Processed Dataset for: Cascaded Machine Learning Integration of Biochemical, Molecular, and Clinical Features for Multi-Class Acute Coronary Syndrome Classification
  Acute Coronary SyndromeMachine LearningLightGBMlncRNACardiovascular Disease
  datacite El-Attar, Noha 2026 置信度 0.66
• Processed Dataset for: Cascaded Machine Learning Integration of Biochemical, Molecular, and Clinical Features for Multi-Class Acute Coronary Syndrome Classification
  Acute Coronary SyndromeMachine LearningLightGBMlncRNACardiovascular Disease
  datacite El-Attar, Noha 2026 置信度 0.66
• A Multimodal Artificial Intelligence Framework for Diabetes Risk Prediction and Diabetic Retinopathy Classification using Clinical and Retinal Data
  Diabetes mellitus is a major chronic disease for which timely risk identification and screening can support earlier clinical intervention. Artificial intelligence provides opportunities to analyse both structured clinical measurements and retinal fundus images…
  datacite Shubhangi Ojha 2026 置信度 0.66 Artificial intelligencediabetes predictiondiabetic retinopathyretinal fundus imagingResNet-50
• A Multimodal Artificial Intelligence Framework for Diabetes Risk Prediction and Diabetic Retinopathy Classification using Clinical and Retinal Data
  Diabetes mellitus is a major chronic disease for which timely risk identification and screening can support earlier clinical intervention. Artificial intelligence provides opportunities to analyse both structured clinical measurements and retinal fundus images…
  datacite Shubhangi Ojha 2026 置信度 0.66 Artificial intelligencediabetes predictiondiabetic retinopathyretinal fundus imagingResNet-50
• Cognitive Retrain: A Web-Based Cognitive Skill Enhancement and Early Detection System for Children with ASD And Dyslexia
  Early detection and continuous therapeutic intervention are critical for children facing cognitive learning challenges, particularly Autism Spectrum Disorder (ASD) and Dyslexia. Traditional clinical diagnostic methodologies are resource-intensive, highly susce…
  datacite Mr. M. Narsimhulu, K. Guna Sai, G. Gokul Kashyap, Gayathri Mangalarapu 等 2026 置信度 0.66 Machine LearningAutism Spectrum DisorderDyslexiaGamified LearningRetrieval-Augmented Generation
• Cognitive Retrain: A Web-Based Cognitive Skill Enhancement and Early Detection System for Children with ASD And Dyslexia
  Early detection and continuous therapeutic intervention are critical for children facing cognitive learning challenges, particularly Autism Spectrum Disorder (ASD) and Dyslexia. Traditional clinical diagnostic methodologies are resource-intensive, highly susce…
  datacite Mr. M. Narsimhulu, K. Guna Sai, G. Gokul Kashyap, Gayathri Mangalarapu 等 2026 置信度 0.66 Machine LearningAutism Spectrum DisorderDyslexiaGamified LearningRetrieval-Augmented Generation
• External validation of prediction models for induction of labor outcomes: Individual Participant Data (IPD) Meta-Analysis – A study protocol
  This protocol is a systematic review to identify and select robust induction of labor (IOL) outcome prediction models to externally validate selected clinical prediction models. We will use individual participant data (IPD) from published randomised controlled…
  datacite Sofonyas Abebaw Tiruneh, Yanan Hu, Ling Shan Au, Ben W Mol 等 2026 置信度 0.66 Medicine and Health SciencesCeasrean sectionClinical prediction modelInduction of labourMachine learning
• Artificial Intelligence-Enabled Wearable Devices for Cardiovascular Disease Screening, Monitoring, and Intervention: An Umbrella Review of Systematic Reviews
  Background Cardiovascular disease (CVD) remains the top cause of global mortality and imposes heavy chronic disease burden worldwide. In China, the prevalence and mortality of CVD have risen sharply over the past decades, accompanied by younger onset age and m…
  datacite 薛则佩, 丁雄, Maoyi Tian, Ning Tang 等 2026 置信度 0.66 Health Information TechnologyDiseasesCardiologyPublic HealthMedicine and Health Sciences
• Digital Intelligence technology empowers interprofessional collaboration and the well-being of medical social workers: a scoping review on health promotion for medical social workers
  Health and social workers (HSWs) and community health workers (CHWs) are critical to health equity in low- and middle-income countries (LMICs), yet they face persistent knowledge gaps, resource constraints, and limited institutional support. Digital technologi…
  datacite jiyan ma, YUKE DAI, jie kang 2026 置信度 0.66 Clinical and Medical Social WorkMedicine and Health SciencesPublic Affairs, Public Policy and Public AdministrationSocial WelfareMental and Social Health
• A Multi-Omic Signature of Diabetes-Associated Pancreatic Cancer for Predicting Clinical Outcomes and Immunotherapy Response
  This is a fully computational, hypothesis-driven bioinformatics study. We will integrate publicly available transcriptomic, proteomic, metabolomic, and clinical data from PDAC patients with documented diabetes status. The study will involve: Data curation and …
  datacite PAWAN kadwe 2026 置信度 0.66 Medicine and Health SciencesLife Sciencescancer
• Real-World Data Analytics in Biomedical Research
  Real-world data (RWD) -- information collected from routine clinical care, insurance claims, patient registries, wearabledevices, and patient-reported outcomes -- represents an increasingly important complement to randomised controlledtrials in biomedical rese…
  datacite Marco Klein, Oscar Bianchi 2026 置信度 0.66 real-world data; real-world evidence; causal inference; target trial emulation; propensity score; comparative effectiveness; pharmacoepidemiology; observational research
• Real-World Data Analytics in Biomedical Research
  Real-world data (RWD) -- information collected from routine clinical care, insurance claims, patient registries, wearabledevices, and patient-reported outcomes -- represents an increasingly important complement to randomised controlledtrials in biomedical rese…
  datacite Marco Klein, Oscar Bianchi 2026 置信度 0.66 real-world data; real-world evidence; causal inference; target trial emulation; propensity score; comparative effectiveness; pharmacoepidemiology; observational research
• Predictive Modeling of Host–Pathogen Interactions
  Host-pathogen interactions (HPIs) -- the molecular, cellular, and immunological interplay between pathogens and theirhosts -- determine infection outcomes, pathogen virulence, host immune response, and therapeutic vulnerabilities.Predictive modelling of HPIs s…
  datacite Hugo Novak, Anna Garcia, Noah Moreau 2024 置信度 0.66 host-pathogen interactions; protein-protein interactions; infection biology; vaccine design; antimicrobial discovery; immune response; pathogen genomics; structural biology
• Predictive Modeling of Host–Pathogen Interactions
  Host-pathogen interactions (HPIs) -- the molecular, cellular, and immunological interplay between pathogens and theirhosts -- determine infection outcomes, pathogen virulence, host immune response, and therapeutic vulnerabilities.Predictive modelling of HPIs s…
  datacite Hugo Novak, Anna Garcia, Noah Moreau 2024 置信度 0.66 host-pathogen interactions; protein-protein interactions; infection biology; vaccine design; antimicrobial discovery; immune response; pathogen genomics; structural biology
• Validating objective and scalable speech markers of depression across two independent psychiatric cohorts
  Abstract Background Using speech as objective markers for major depressive disorder (MDD) has shown promise, yet their generalizability across clinical settings remains largely unvalidated. Objective This study aimed to validate previously identified speech ma…
  datacite Felix Menne, Felix Dörr, Johannes Tröger, Alexandra König 等 2026 置信度 0.66 MedicineSociologyBiological Sciences not elsewhere classifiedScience PolicyMental Health
• Validating objective and scalable speech markers of depression across two independent psychiatric cohorts
  Abstract Background Using speech as objective markers for major depressive disorder (MDD) has shown promise, yet their generalizability across clinical settings remains largely unvalidated. Objective This study aimed to validate previously identified speech ma…
  datacite Felix Menne, Felix Dörr, Johannes Tröger, Alexandra König 等 2026 置信度 0.66 MedicineSociologyBiological Sciences not elsewhere classifiedScience PolicyMental Health
• A machine learning framework for cost-efficient resource allocation: evidence from HER2-positive breast cancer diagnosis in low-resource settings
  Abstract Accurate identification of HER2-positive breast cancer is essential for treatment planning; however, diagnostic decision-making in resource-constrained healthcare systems is challenged by class imbalance, which can substantially reduce the detection o…
  datacite Hoda Waguih 2026 置信度 0.66 Space ScienceMedicineBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedCancer
• A machine learning framework for cost-efficient resource allocation: evidence from HER2-positive breast cancer diagnosis in low-resource settings
  Abstract Accurate identification of HER2-positive breast cancer is essential for treatment planning; however, diagnostic decision-making in resource-constrained healthcare systems is challenged by class imbalance, which can substantially reduce the detection o…
  datacite Hoda Waguih 2026 置信度 0.66 Space ScienceMedicineBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedCancer
• Privacy-Preserving Federated Learning Framework for ICU Patient Monitoring and Decision Support in Hospitals
  The increasing digitization of healthcare systems has led to the generation of large-scale ICU patient data across hospitals. However, centralized machine learning approaches pose significant privacy risks, limiting data sharing across institutions. This paper…
  datacite Mr. B. Sundaresan, Bernus A, Jayamadhavan V, Sam Benny J Department of Computer Science & Engineering Velammal Institute of Technology, Panchetti, DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE R.M.K. College of Engineering and Technology, MISSILE MAN SCIENTIFIC AND RESEARCH PUBLICATIONS 2026 置信度 0.66
• Privacy-Preserving Federated Learning Framework for ICU Patient Monitoring and Decision Support in Hospitals
  The increasing digitization of healthcare systems has led to the generation of large-scale ICU patient data across hospitals. However, centralized machine learning approaches pose significant privacy risks, limiting data sharing across institutions. This paper…
  datacite Mr. B. Sundaresan, Bernus A, Jayamadhavan V, Sam Benny J Department of Computer Science & Engineering Velammal Institute of Technology, Panchetti, DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE R.M.K. College of Engineering and Technology, MISSILE MAN SCIENTIFIC AND RESEARCH PUBLICATIONS 2026 置信度 0.66
• Machine Learning for Antimicrobial Resistance Prediction
  Antimicrobial resistance threatens modern medicine by rendering antibiotics ineffective against bacterial pathogens, andmachine learning models that predict resistance phenotypes from bacterial genome sequences offer rapid alternatives toculture-based suscepti…
  datacite Jonas Garcia, Laura Hansen, Clara Petrov 2023 置信度 0.66 antimicrobial resistance; machine learning; AMR prediction; bacterial genomics; AMPI; resistance genes; whole-genome sequencing; MIC prediction; clinical microbiology; susceptibility testing; CARD; ResFinder
• Machine Learning for Antimicrobial Resistance Prediction
  Antimicrobial resistance threatens modern medicine by rendering antibiotics ineffective against bacterial pathogens, andmachine learning models that predict resistance phenotypes from bacterial genome sequences offer rapid alternatives toculture-based suscepti…
  datacite Jonas Garcia, Laura Hansen, Clara Petrov 2023 置信度 0.66 antimicrobial resistance; machine learning; AMR prediction; bacterial genomics; AMPI; resistance genes; whole-genome sequencing; MIC prediction; clinical microbiology; susceptibility testing; CARD; ResFinder
• Информационная модель прогнозирования тяжести заболевания
  Данная работа посвящена разработке улучшенной информационной модели прогнозирования тяжести внебольничной пневмонии у детей методами машинного обучения. Задачи, которые решались в ходе исследования: 1. Обзор предметной области: клинические особенности внебольн…
  datacite Зиссерман, Елена Дмитриевна 2026 置信度 0.66 внебольничная пневмониямашинное обучениелогистическая регрессияслучайный лесградиентный бустинг
• FluSight: Two-Stage k-mer Random Forest Framework for Influenza A Zoonotic Risk Prediction
  Description This release archives the exact version of the FluSight pipeline submitted to the Journal of Medical Virology. FluSight is a hierarchical machine learning framework designed for alignment-free prediction of Influenza A host adaptation and zoonotic …
  datacite Chauhan, Maitry, Gupta, Aryan, Karthik, Shivram, Sharma, Akshi 等 2026 置信度 0.66
• FluSight: Two-Stage k-mer Random Forest Framework for Influenza A Zoonotic Risk Prediction
  Description This release archives the exact version of the FluSight pipeline submitted to the Journal of Medical Virology. FluSight is a hierarchical machine learning framework designed for alignment-free prediction of Influenza A host adaptation and zoonotic …
  datacite Chauhan, Maitry, Gupta, Aryan, Karthik, Shivram, Sharma, Akshi 等 2026 置信度 0.66
• AI-Based Osteoporosis Detection Using Clinical Bone Densitometry Data and Deep Learning Techniques
  Osteoporosis is a progressive bone disease characterized by decreased bone mineral density (BMD) and an increased risk of fractures, especially among elderly individuals and postmenopausal women. Early detection is crucial to prevent severe complications and i…
  datacite IJISEA 2026 置信度 0.66
• AI-Based Osteoporosis Detection Using Clinical Bone Densitometry Data and Deep Learning Techniques
  Osteoporosis is a progressive bone disease characterized by decreased bone mineral density (BMD) and an increased risk of fractures, especially among elderly individuals and postmenopausal women. Early detection is crucial to prevent severe complications and i…
  datacite IJISEA 2026 置信度 0.66
• Explainable Transformer Models for Clinical Prediction Tasks on Structured Electronic Health Records
  Predictive models over structured electronic health records (EHRs) remain central to machine learning for healthcare, but few have jointly emphasized quantitative laboratory information and interpretability with respect to input medical events. We present BERT…
  datacite Du, Jun Ni, Adamek, Lukas, Kryukov, Maxim, Dormont, Flavio 等 2026 置信度 0.66 Machine Learning (cs.LG)FOS: Computer and information sciences
• Flow Matching Meets 3D Curvilinear Structure Segmentation in Medical Imaging
  Segmentation of curvilinear anatomical structures in 3D medical images remains challenging due to complex topology, severe class imbalance, weak contrast, and large variations in structure morphology. While deep learning approaches for 3D curvilinear segmentat…
  datacite Moctar, Sidi Mohamed Sid'El, Vitry, Nicolas, Bouvrais, Hélène 2026 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)Machine Learning (cs.LG)Quantitative Methods (q-bio.QM)FOS: Computer and information sciencesFOS: Biological sciences
• In a heartbeat: discovering complex cardiac motion signatures with machine learning
  Cardiac remodelling describes a range of adaptive responses to stress across physiological scales, governed by diverse molecular pathways. Traditional imaging-based assessments primarily rely on volumetric metrics, which serve as global indicators of function …
  datacite Schiratti, Pierre-Raphaël 2025 置信度 0.66
• Clinical application of artificial intelligence to improve glaucoma care using imaging modalities
  Glaucoma, a leading cause of irreversible blindness, presents significant challenges for early diagnosis and timely intervention due to its asymptomatic nature and subtle clinical morphology. Early detection and intervention are critical for preventing the dis…
  datacite Abadh Chaurasia 2026 置信度 0.66
• Clinical application of artificial intelligence to improve glaucoma care using imaging modalities
  Glaucoma, a leading cause of irreversible blindness, presents significant challenges for early diagnosis and timely intervention due to its asymptomatic nature and subtle clinical morphology. Early detection and intervention are critical for preventing the dis…
  datacite Abadh Chaurasia 2026 置信度 0.66
• Martingale R-learner: Estimating Time-varying Heterogeneous Treatment Effects for Time-to-event Outcomes
  Biological research and clinical evidence suggest that treatment response may vary substantially along characteristics, such as comorbidities, genetic variants, environmental, or socio-economic factors. Future precision medicine requires accurate assessment of…
  datacite Hou, Jue, Qi, Yuchen, Xu, Ronghui 2026 置信度 0.66 Methodology (stat.ME)FOS: Computer and information sciences
• A Two-Stage Time-Aware Transformer for Short-Horizon AECOPD Risk Prediction
  Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) can worsen rapidly, making timely prediction a clinical priority. Most existing machine learning approaches rely on episodically collected clinical variables, introducing delays that limit th…
  datacite Wang, Dongyang, Qu, Weihao, Zheng, Ling, Pan, Haowen 2026 置信度 0.66 Machine Learning (cs.LG)FOS: Computer and information sciences
• Operational Outcomes of Artificial Intelligence–Enabled Digital Interventions for Patient Flow and Capacity Management in Hospital Emergency Departments: A Scoping Review
  This scoping review aims to map the operational outcomes and organizational and implementation determinants reported following the prospective or routine implementation of artificial intelligence (AI)–enabled digital interventions in hospital emergency departm…
  datacite Gonzalo Alberto Peralta-Jiménez 2026 置信度 0.66 Health Information TechnologyOther Medicine and Health SciencesMedicine and Health SciencesHealth and Medical Administrationartificial intelligence
• Synthetic Turkish Clinical Event Dataset for Temporal Risk Prediction, Sequence Modeling, and NLP
  This dataset contains a synthetic Turkish clinical event dataset designed for temporal risk prediction, sequence modeling, and healthcare-related machine learning research. The dataset simulates longitudinal patient records, including visits, diagnoses, lab te…
  datacite Bayankulu, Senih 2026 置信度 0.66 synthetic-datahealthcareclinical-datatemporal-datasequence-modeling
• Synthetic Turkish Clinical Event Dataset for Temporal Risk Prediction, Sequence Modeling, and NLP
  This dataset contains a synthetic Turkish clinical event dataset designed for temporal risk prediction, sequence modeling, and healthcare-related machine learning research. The dataset simulates longitudinal patient records, including visits, diagnoses, lab te…
  datacite Bayankulu, Senih 2026 置信度 0.66 synthetic-datahealthcareclinical-datatemporal-datasequence-modeling
• Arabic Parkinson's Disease Speech Dataset
  This dataset contains audio recordings collected to investigate acoustic biomarkers and machine learning models for detecting Parkinson’s Disease (PD) in native Arabic speakers. Designed to support voice pathology detection, acoustic feature extraction, and cr…
  datacite Hassanat, Ahmad, Almahadin, Alaa O. 2026 置信度 0.66 Parkinson's Disease, Arabic Speech Dataset, Audio Processing, Acoustic Biomarkers, Machine Learning, Voice Analysis, Cross-Linguistic Validation
• Arabic Parkinson's Disease Speech Dataset
  This dataset contains audio recordings collected to investigate acoustic biomarkers and machine learning models for detecting Parkinson’s Disease (PD) in native Arabic speakers. Designed to support voice pathology detection, acoustic feature extraction, and cr…
  datacite Hassanat, Ahmad, Almahadin, Alaa O. 2026 置信度 0.66 Parkinson's Disease, Arabic Speech Dataset, Audio Processing, Acoustic Biomarkers, Machine Learning, Voice Analysis, Cross-Linguistic Validation
• Synthetic Dataset for Detecting the Relationship Between Psychological Illnesses and Criminal Tendency Patterns Using Machine Learning
  This record contains synthetic datasets generated for the study titled “Detecting the Relationship Between Psychological Illnesses and Criminal Tendencies Using Machine Learning.” The datasets were created for research and machine learning modeling purposes an…
  datacite Bilgin, Sümeyra, Vural, Mehmet Sait 2026 置信度 0.66
• Synthetic Dataset for Detecting the Relationship Between Psychological Illnesses and Criminal Tendency Patterns Using Machine Learning
  This record contains synthetic datasets generated for the study titled “Detecting the Relationship Between Psychological Illnesses and Criminal Tendencies Using Machine Learning.” The datasets were created for research and machine learning modeling purposes an…
  datacite Bilgin, Sümeyra, Vural, Mehmet Sait 2026 置信度 0.66
• Explainable Machine Learning and Deep Learning for Alzheimer's Disease Detection from Structural MRI and Clinical Data
  datacite Chennoufi, Ines, Chih, Chaima Malak 2026 置信度 0.66
• Explainable Machine Learning and Deep Learning for Alzheimer's Disease Detection from Structural MRI and Clinical Data
  datacite Chennoufi, Ines, Chih, Chaima Malak 2026 置信度 0.66
• HF-ETIOLOGY: Program Team Update Meeting (August 2026)
  This is a presentation from the August 2026 update to the NIH Program Team for the HF-ETIOLOGY Project.
  datacite Luo, Yuan, Cheng, Feixiong, Holmes, Kristi, Wang, Fei 2026 置信度 0.66 Behavioral Sciences/methodsBiological FactorsClinical MedicineData Collection/statistics & numerical dataData Curation/statistics & numerical data
• HF-ETIOLOGY: Program Team Update Meeting (August 2026)
  This is a presentation from the August 2026 update to the NIH Program Team for the HF-ETIOLOGY Project.
  datacite Luo, Yuan, Cheng, Feixiong, Holmes, Kristi, Wang, Fei 2026 置信度 0.66 Behavioral Sciences/methodsBiological FactorsClinical MedicineData Collection/statistics & numerical dataData Curation/statistics & numerical data
• Comprehensive Evaluation of Support Vector Machine Models Based on Kernels for Predicting Multiple Diseases
  In today's digital age, data is invaluable, and massive amounts of data have been produced in every field imaginable. Reports from the healthcare sector often contain details about patients' health. By having this clinical expertise, we are better able to dete…
  datacite G Swathika, K Venkata Ramaiah 2026 置信度 0.66
• Comprehensive Evaluation of Support Vector Machine Models Based on Kernels for Predicting Multiple Diseases
  In today's digital age, data is invaluable, and massive amounts of data have been produced in every field imaginable. Reports from the healthcare sector often contain details about patients' health. By having this clinical expertise, we are better able to dete…
  datacite G Swathika, K Venkata Ramaiah 2026 置信度 0.66
• What are the potential benefits and limitations of using machine learning algorithms to predict arrhythmogenic events in patients with long QT syndrome?
  Machine learning algorithms offer potential benefits in predicting arrhythmogenic events in long QT syndrome, though challenges around data quality, validation, and ethical issues present significant hurdles for clinical implementation.
  datacite Tripdatabase 2026 置信度 0.66 machine learningarrhythmogenic eventslong QT syndromepredictive algorithmscardiology
• What are the potential benefits and limitations of using machine learning algorithms to predict arrhythmogenic events in patients with long QT syndrome?
  Machine learning algorithms offer potential benefits in predicting arrhythmogenic events in long QT syndrome, though challenges around data quality, validation, and ethical issues present significant hurdles for clinical implementation.
  datacite Tripdatabase 2026 置信度 0.66 machine learningarrhythmogenic eventslong QT syndromepredictive algorithmscardiology
• Code for: GRAD: A Two-Stage Machine Learning Algorithm Resolves the Plasma p-Tau217 Diagnostic Gray Zone for Amyloid PET Prediction
  Two-stage diagnostic algorithm (Gatekeeper-Reflex for Alzheimer's Diagnostics) that resolves diagnostic uncertainty in plasma p-tau217 testing by combining a univariate logistic regression screen with a multi-marker random forest classifier for gray zone cases…
  datacite Parankusham, Harthik, Vanderlip, Casey, Birkenbihl, Colin Jan, Krishna, Eashwar 等 2026 置信度 0.66 Alzheimer's diseaseplasma biomarkersp-tau217amyloid PETmachine learning
• Data and Code for Machine Learning Based Reference Assisted Signal Recovery Under Anatomical Domain Shift in Simulated Radiofrequency Fracture Sensing
  Version 1.1.0 of the public data-and-code release supporting the article “Machine Learning Based Reference Assisted Signal Recovery Under Anatomical Domain Shift in Simulated Radiofrequency Fracture Sensing”. The release contains the canonical processed featur…
  datacite AlDelemy, Ahmad, Al Dulaimi, Ali, Abd-Alhameed, Raed 2026 置信度 0.66 radiofrequency fracture sensingdeep learningmachine learninganatomical domain shiftdomain generalisation
• Data and Code for Machine Learning Based Reference Assisted Signal Recovery Under Anatomical Domain Shift in Simulated Radiofrequency Fracture Sensing
  Version 1.1.0 of the public data-and-code release supporting the article “Machine Learning Based Reference Assisted Signal Recovery Under Anatomical Domain Shift in Simulated Radiofrequency Fracture Sensing”. The release contains the canonical processed featur…
  datacite AlDelemy, Ahmad, Al Dulaimi, Ali, Abd-Alhameed, Raed 2026 置信度 0.66 radiofrequency fracture sensingdeep learningmachine learninganatomical domain shiftdomain generalisation
• A Labeled Accelerometry Dataset of Steps and Postures Across Diverse Mobility and Frailty Levels in Older Adults in a Hospital Setting
  The Mobility in Geriatrics (Mobi-G) dataset is an open-access dataset designed to support the development, validation, and benchmarking of machine learning algorithms for posture classification and step counting in older adults. The dataset includes ankle-worn…
  datacite Lanoie, Annik, Cheung, Weng-Jy Cheung, Nguyen, Quoc Dinh 2026 置信度 0.66 Medicine, Health and Life SciencesSensorsAccelerometryGeriatricsMobility
• ARTIFICIAL INTELLIGENCE AND PRECISION MEDICINE IN PARKINSON'S DISEASE: EMERGING DIAGNOSTIC AND THERAPEUTIC APPROACHES
  Background: Parkinson's disease (PD) is heterogeneous, both clinically, genetically and neuropathologically, which presents ongoing challenges for conventional syndromic clinical diagnostic criteria and uniform treatments. Recent advances in biofluid biomarker…
  datacite Payal Patidar, Soma Sekhar Pulamarasetti*, Omkar Rai, Karan Gupta¹, Shivlal Yadav 2026 置信度 0.66
• ARTIFICIAL INTELLIGENCE AND PRECISION MEDICINE IN PARKINSON'S DISEASE: EMERGING DIAGNOSTIC AND THERAPEUTIC APPROACHES
  Background: Parkinson's disease (PD) is heterogeneous, both clinically, genetically and neuropathologically, which presents ongoing challenges for conventional syndromic clinical diagnostic criteria and uniform treatments. Recent advances in biofluid biomarker…
  datacite Payal Patidar, Soma Sekhar Pulamarasetti*, Omkar Rai, Karan Gupta¹, Shivlal Yadav 2026 置信度 0.66
• BIOMARKERS DISCOVERY IN TYPE 2 DIABETES MELLITUS: FROM OMICS TECHNOLOGIES TO CLINICAL PRACTICE
  Background: Type 2 diabetes mellitus (T2DM) is caused by complex pathophysiological processes including progressive insulin resistance, pancreatic β-cell dysfunction, chronic systemic inflammation and altered interorgan metabolic communication1. The ability of…
  datacite Manisha, Soma Sekhar Pulamarasetti*, Omkar Rai, Karan Gupta, Shivlal Yadav 2026 置信度 0.66
• BIOMARKERS DISCOVERY IN TYPE 2 DIABETES MELLITUS: FROM OMICS TECHNOLOGIES TO CLINICAL PRACTICE
  Background: Type 2 diabetes mellitus (T2DM) is caused by complex pathophysiological processes including progressive insulin resistance, pancreatic β-cell dysfunction, chronic systemic inflammation and altered interorgan metabolic communication1. The ability of…
  datacite Manisha, Soma Sekhar Pulamarasetti*, Omkar Rai, Karan Gupta, Shivlal Yadav 2026 置信度 0.66
• Artificial Intelligence in Clinical Pharmacy: Current Applications, Challenges, and Future Perspectives – A Narrative Literature Review
  Background Artificial intelligence (AI) is rapidly transforming healthcare by enabling the analysis of large and complex datasets and supporting clinical decision-making. Clinical pharmacy is an emerging area in which AI can assist with medication management, …
  datacite Dr. Keerthika R* 2026 置信度 0.66 Artificial intelligence; clinical pharmacy; machine learning; generative AI; ChatGPT; medication safety; pharmacovigilance; clinical decision support; personalized medicine; pharmacy practice.
• Artificial Intelligence in Clinical Pharmacy: Current Applications, Challenges, and Future Perspectives – A Narrative Literature Review
  Background Artificial intelligence (AI) is rapidly transforming healthcare by enabling the analysis of large and complex datasets and supporting clinical decision-making. Clinical pharmacy is an emerging area in which AI can assist with medication management, …
  datacite Dr. Keerthika R* 2026 置信度 0.66 Artificial intelligence; clinical pharmacy; machine learning; generative AI; ChatGPT; medication safety; pharmacovigilance; clinical decision support; personalized medicine; pharmacy practice.
• Enfoque diagnóstico de las asincronías paciente-ventilador en pacientes en estado crítico: Scoping review
  This scoping review identifies that automated systems based on machine learning represent a promising direction in the study of PVA. The literature suggests their potential to deliver accurate, real-time classification, enhancing clinical decision-making and i…
  datacite Julian Cortes 2026 置信度 0.66 Medicine and Health SciencesMedical SpecialtiesCritical Care
• Computational models of seizure activity and brain state dynamics in epilepsy
  Epilepsy is a prevalent neurological disorder characterized by recurrent spontaneous seizures, whose occurrence varies substantially both between and within individuals. This variability is increasingly understood to be structured by underlying circadian and u…
  datacite Chybowski, Bartłomiej Szymon 2026 置信度 0.66 epileptic seizuresseizure detectionEEG recordingscomputational modelsrhythm information
• Shahram-Bioinfo/HLA-I-Multiomics-HCC: HLA-I Multiomics HCC Analysis - Initial Release
  This release contains the full analysis pipeline for: "HLA Class I Expression and Ratios as Diagnostic and Predictive Biomarkers in Hepatocellular Carcinoma: A Multi-Omics Study" Includes: Allele-specific analysis Neoantigen prediction (netMHCpan pipeline) Cli…
  datacite Shahram Aliyari 2026 置信度 0.66
• Shahram-Bioinfo/HLA-I-Multiomics-HCC: HLA-I Multiomics HCC Analysis - Initial Release
  This release contains the full analysis pipeline for: "HLA Class I Expression and Ratios as Diagnostic and Predictive Biomarkers in Hepatocellular Carcinoma: A Multi-Omics Study" Includes: Allele-specific analysis Neoantigen prediction (netMHCpan pipeline) Cli…
  datacite Shahram Aliyari 2026 置信度 0.66
• Explainable AI-Based Disease Prediction using IoT Sensors for Smart Healthcare Systems
  The rapid growth of chronic diseases and the increasing demand for remote healthcare services have accelerated the adoption of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in smart healthcare environments. Conventional healthcare syst…
  datacite Dhulipalla Rajesh Kumar, Alla Sambasiva Rao 2026 置信度 0.66
• Explainable AI-Based Disease Prediction using IoT Sensors for Smart Healthcare Systems
  The rapid growth of chronic diseases and the increasing demand for remote healthcare services have accelerated the adoption of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in smart healthcare environments. Conventional healthcare syst…
  datacite Dhulipalla Rajesh Kumar, Alla Sambasiva Rao 2026 置信度 0.66
• Development and internal validation of a machine learning-based disease burden index for irritable bowel syndrome: a multicentre cross-sectional study
  Irritable bowel syndrome (IBS) is one of the most common disorders of gut-brain interaction in gastroenterology clinics worldwide, becoming a significant public health burden. This study aims to provide an exploratory approach for comprehensive assessment of I…
  datacite Yanbin Wei, Heyang Zhang, Nan Wang, Haifeng Jin 等 2026 置信度 0.66 MedicineImmunologyBiological Sciences not elsewhere classifiedScience PolicyHematology
• Development and internal validation of a machine learning-based disease burden index for irritable bowel syndrome: a multicentre cross-sectional study
  Irritable bowel syndrome (IBS) is one of the most common disorders of gut-brain interaction in gastroenterology clinics worldwide, becoming a significant public health burden. This study aims to provide an exploratory approach for comprehensive assessment of I…
  datacite Yanbin Wei, Heyang Zhang, Nan Wang, Haifeng Jin 等 2026 置信度 0.66 MedicineImmunologyBiological Sciences not elsewhere classifiedScience PolicyHematology
• Synthetic Medical Records Using Generative Adversarial Networks (GANs)
  The quick data driven technology adoption of the health care sector has extinguished the notion that we require large volumes and superiorities of medical data to drive the machine learning, predictive analytics and clinical decision support systems. Simultane…
  datacite Pooja Dhankade, Dr. Pravin Kumar Malviya 2026 置信度 0.66
• Synthetic Medical Records Using Generative Adversarial Networks (GANs)
  The quick data driven technology adoption of the health care sector has extinguished the notion that we require large volumes and superiorities of medical data to drive the machine learning, predictive analytics and clinical decision support systems. Simultane…
  datacite Pooja Dhankade, Dr. Pravin Kumar Malviya 2026 置信度 0.66
• mlrivera123/LLM-Framework-for-Ranked-Diagnosis-Suggestion: Aligning AI with Clinical Workflow: A Probabilistic LLM Framework for Ranked Diagnosis Suggestion from Unstructured Clinical Notes
  Clinical notes are a form of unstructured data that contain a wealth of information such as patient symptoms, disease trajectory and management. While they are the most versatile and informative healthcare data, their annotation for machine learning requires s…
  datacite Max Rivera 2026 置信度 0.66
• mlrivera123/LLM-Framework-for-Ranked-Diagnosis-Suggestion: Aligning AI with Clinical Workflow: A Probabilistic LLM Framework for Ranked Diagnosis Suggestion from Unstructured Clinical Notes
  Clinical notes are a form of unstructured data that contain a wealth of information such as patient symptoms, disease trajectory and management. While they are the most versatile and informative healthcare data, their annotation for machine learning requires s…
  datacite Max Rivera 2026 置信度 0.66
• A Machine Learning-Based Raman Spectroscopic Assay for the Identification of Burkholderia mallei and Related Species
  Burkholderia (B.) mallei, the causative agent of glanders, and B. pseudomallei, the causative agent of melioidosis in humans and animals, are genetically closely related. The high infectious potential of both organisms, their serological cross-reactivity, and …
  datacite Silge, Anja, Moawad, Amira A., Bocklitz, Thomas, Fischer, Katja 等 2019 置信度 0.66 540Burkholderia malleiBurkholderia pseudomalleiGlandersHeat inactivation
• Predictive Modeling of Antibiotic Susceptibility in E. Coli Strains Using the U-Net Network and One-Class Classification
  The antibiotic resistance of bacterial pathogens has become one of the most serious global health issues due to misusing and overusing of antibiotics. Recently, different technologies were developed to determine bacteria susceptibility towards antibiotics; how…
  datacite Ali, Nairveen, Kirchhoff, Johanna, Onoja, Patrick Igoche, Tannert, Astrid 等 2020 置信度 0.66 004621.3E. coli strainsAntibiotic resistanceOne-class SVM
• Semantic segmentation of non-linear multimodal images for disease grading of inflammatory bowel disease: A segnet-based application
  Non-linear multimodal imaging, the combination of coherent anti-stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF) and second harmonic generation (SHG), has shown its potential to assist the diagnosis of different inflammatory bowel disease…
  datacite Pradhan, Pranita, Meyer, Tobias, Vieth, Michael, Stallmach, Andreas 等 2019 置信度 0.66 610004Inflammatory Bowel DiseaseNon-linear Multimodal ImagingSemantic Segmentation
• Towards the automatic detection of social biomarkers in autism spectrum disorder: introducing the simulated interaction task (SIT)
  Social interaction deficits are evident in many psychiatric conditions and specifically in autism spectrum disorder (ASD), but hard to assess objectively. We present a digital tool to automatically quantify biomarkers of social interaction deficits: the simula…
  datacite Drimalla, Hanna, Scheffer, Tobias, Landwehr, Niels, Baskow, Irina 等 2020 置信度 0.66 610audio recordingautismcomparative studyelectromyogram
• Calibrating mini-mental state examination scores to predict misdiagnosed dementia patients
  Mini-Mental State Examination (MMSE) is used as a diagnostic test for dementia to screen a patient’s cognitive assessment and disease severity. However, these examinations are often inaccurate and unreliable either due to human error or due to patients’ physic…
  datacite Vyas, Akhilesh, Aisopos, Fotis, Vidal, Maria-Esther, Garrard, Peter 等 2021 置信度 0.66 600610ClassificationDementiaMachine learning
• Identifying the presence and severity of dementia by applying interpretable machine learning techniques on structured clinical records
  Background: Dementia develops as cognitive abilities deteriorate, and early detection is critical for effective preventive interventions. However, mainstream diagnostic tests and screening tools, such as CAMCOG and MMSE, often fail to detect dementia accuratel…
  datacite Vyas, Akhilesh, Aisopos, Fotis, Vidal, Maria-Esther, Garrard, Peter 等 2022 置信度 0.66 610CAMCOGData scienceDementiaLIME
• A Review on Data Fusion of Multidimensional Medical and Biomedical Data
  Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characterization of s…
  datacite Azam, Kazi Sultana Farhana, Ryabchykov, Oleg, Bocklitz, Thomas 2022 置信度 0.66 540computed tomographydata fusiondeep learningfluorescence lifetime imaging microscopy
• Cognitive Computing and Advanced AI Systems
  We stand at a pivotal moment in technological history, defined not by isolated breakthroughs, but by the powerful convergence of four foundational paradigms: the Internet of Things (IoT), Blockchain, Artificial Intelligence (AI), and Machine Learning (ML). For…
  datacite Dr Jayaram C V, Archana Das, Dr. Niranjan KR, Arun Kashyap 等 2026 置信度 0.66
• Cognitive Computing and Advanced AI Systems
  We stand at a pivotal moment in technological history, defined not by isolated breakthroughs, but by the powerful convergence of four foundational paradigms: the Internet of Things (IoT), Blockchain, Artificial Intelligence (AI), and Machine Learning (ML). For…
  datacite Dr Jayaram C V, Archana Das, Dr. Niranjan KR, Arun Kashyap 等 2026 置信度 0.66
• Wearable AI Systems for Health Prediction
  Wearable AI systems integrate miniaturised biosensors with on-device or cloud-based machine learning to enablecontinuous, real-time health prediction from passively collected physiological signals. Advances in edge computing,energy-efficient neural network arc…
  datacite Marco Hansen, Pierre Jensen 2023 置信度 0.66 wearable AI; health prediction; continuous monitoring; federated learning; cardiovascular risk; sleep apnoea; hypoglycaemia prediction; edge AI
• Wearable AI Systems for Health Prediction
  Wearable AI systems integrate miniaturised biosensors with on-device or cloud-based machine learning to enablecontinuous, real-time health prediction from passively collected physiological signals. Advances in edge computing,energy-efficient neural network arc…
  datacite Marco Hansen, Pierre Jensen 2023 置信度 0.66 wearable AI; health prediction; continuous monitoring; federated learning; cardiovascular risk; sleep apnoea; hypoglycaemia prediction; edge AI
• Vaccine Development and The Role of Artificial Intelligence
  Artificial Intelligence (AI) has become a transformative technology in modern pandemic preparedness and response, enabling significant advances across public health, epidemiology, diagnostics, and vaccine research. This review explores the broad applications o…
  datacite Thota. Srinivas Rao, Dr. T. Thangabalan, D. Akash*, R. Pishan, T. Devi Sowjanya 2026 置信度 0.66 Artificial Intelligence (AI), transformative technology, modern pandemic preparedness and response
• Vaccine Development and The Role of Artificial Intelligence
  Artificial Intelligence (AI) has become a transformative technology in modern pandemic preparedness and response, enabling significant advances across public health, epidemiology, diagnostics, and vaccine research. This review explores the broad applications o…
  datacite Thota. Srinivas Rao, Dr. T. Thangabalan, D. Akash*, R. Pishan, T. Devi Sowjanya 2026 置信度 0.66 Artificial Intelligence (AI), transformative technology, modern pandemic preparedness and response
• Integrated AI-based Care Model Library I
  Deliverable D3.7, titled “Integrated AI-based Care Model Library I”, consolidates the state-of-the-art (SOTA) analysis, and the methodologies explored in tasks T3.5 – “Explainable Models and Algorithms for Trustworthy AI” and T3.6 – “Integrated Care Model Libr…
  datacite Tsitiridis, Aristeidis, Tsolis, Dimitrios, Lykothanasi, Kalliopi Klelia, Tsoukalos, Dimitrios 等 2026 置信度 0.66 XAIICLMEXPLANAIBLE AIIntegrated Care Model Library
• Integrated AI-based Care Model Library I
  Deliverable D3.7, titled “Integrated AI-based Care Model Library I”, consolidates the state-of-the-art (SOTA) analysis, and the methodologies explored in tasks T3.5 – “Explainable Models and Algorithms for Trustworthy AI” and T3.6 – “Integrated Care Model Libr…
  datacite Tsitiridis, Aristeidis, Tsolis, Dimitrios, Lykothanasi, Kalliopi Klelia, Tsoukalos, Dimitrios 等 2026 置信度 0.66 XAIICLMEXPLANAIBLE AIIntegrated Care Model Library
• APPLIED MATHEMATICS FOR REAL-WORLD PROBLEM SOLVING
  The modern world runs on data, algorithms, and continuous optimization. From the smartphone applications that route daily traffic to the machine learning frameworks powering global industries, the foundational engine driving these advancements is applied mathe…
  datacite Dr. Malabika Adak, Dr. Gauri Ghule, Mr. Dnyaneshwar P. Bawane, Dr.(Mrs.) Anushree A. Aserkar 等 2026 置信度 0.66
• APPLIED MATHEMATICS FOR REAL-WORLD PROBLEM SOLVING
  The modern world runs on data, algorithms, and continuous optimization. From the smartphone applications that route daily traffic to the machine learning frameworks powering global industries, the foundational engine driving these advancements is applied mathe…
  datacite Dr. Malabika Adak, Dr. Gauri Ghule, Mr. Dnyaneshwar P. Bawane, Dr.(Mrs.) Anushree A. Aserkar 等 2026 置信度 0.66
• APPLIED MATHEMATICS FOR REAL-WORLD PROBLEM SOLVING
  The modern world runs on data, algorithms, and continuous optimization. From the smartphone applications that route daily traffic to the machine learning frameworks powering global industries, the foundational engine driving these advancements is applied mathe…
  datacite Dr. Malabika Adak, Dr. Gauri Ghule, Mr. Dnyaneshwar P. Bawane, Dr.(Mrs.) Anushree A. Aserkar 等 2026 置信度 0.66
• Wearable sensors and Machine Learning to automatically assess dystonia and chorea [Protocol Scoping Review]
  This scoping review aims to map the current literature on the integration of wearable sensors and machine learning techniques for the automated detection and severity assessment of dystonia and chorea. Following the PRISMA-ScR guidelines, this protocol outline…
  datacite Sonia Pianzi, Marte Apers, Marie Heymans, Jean-Marie Aerts 等 2026 置信度 0.66 Other Rehabilitation and TherapyBiomedical Devices and InstrumentationBiomedicalComputer EngineeringMedicine and Health Sciences
• ROLE OF ARTIFICIAL INTELLIGENCE AS A DIAGNOSTIC TOOL IN FUNCTIONAL ABDOMINAL PAIN IN CHILDREN
  Functional Abdominal Pain Disorders (FAPDs) account for nearly 80% of chronic abdominal pain cases in children and are diagnosed according to Rome IV criteria in the absence of identifiable organic pathology. In classical Ayurveda, this clinical spectrum may b…
  datacite Dr. Ankit Pal* and Asst. Prof. (Dr) Laxmi 2026 置信度 0.66
• ROLE OF ARTIFICIAL INTELLIGENCE AS A DIAGNOSTIC TOOL IN FUNCTIONAL ABDOMINAL PAIN IN CHILDREN
  Functional Abdominal Pain Disorders (FAPDs) account for nearly 80% of chronic abdominal pain cases in children and are diagnosed according to Rome IV criteria in the absence of identifiable organic pathology. In classical Ayurveda, this clinical spectrum may b…
  datacite Dr. Ankit Pal* and Asst. Prof. (Dr) Laxmi 2026 置信度 0.66
• ML-Based Cardiovascular Risk Prediction in Inflammatory Rheumatic Diseases: A Scoping Review Protocol
  1. Background Individuals with inflammatory rheumatic diseases (IRDs) - such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), psoriatic arthritis (PsA), ankylosing spondylitis (AS), and similar conditions- have a much higher risk of cardiovasc…
  datacite Irine Bakhutashvili, Tamuna Jatchvadze 2026 置信度 0.66 AnatomyPhysical Sciences and MathematicsDiseasesCardiologyPublic Health
• A Low-Cost AI-IoT and GSM-Enabled Pediatric Wristband for Continuous Fever Risk Assessment and Emergency Alerting
  This paper presents a low-cost pediatric wearable wristband for continuous fever-risk monitoring using temperature, heart-rate, and motion sensing. The device integrates an ESP32 controller, a DS18B20 temperature sensor, a pulse sensor, an MPU6050 acceleromete…
  datacite Ms. Gauri J. Sutar, Associate Professor Dr. Sarita V. Balshetwar, Assistant Professor Mrs. Rajani M. Mandhare 2026 置信度 0.66
• A Low-Cost AI-IoT and GSM-Enabled Pediatric Wristband for Continuous Fever Risk Assessment and Emergency Alerting
  This paper presents a low-cost pediatric wearable wristband for continuous fever-risk monitoring using temperature, heart-rate, and motion sensing. The device integrates an ESP32 controller, a DS18B20 temperature sensor, a pulse sensor, an MPU6050 acceleromete…
  datacite Ms. Gauri J. Sutar, Associate Professor Dr. Sarita V. Balshetwar, Assistant Professor Mrs. Rajani M. Mandhare 2026 置信度 0.66
• A Prediction of Users Repurchase Based on Machine Learning Theory
  crossref Hanzhe Zhang 2026-01-22T20:58:30Z 置信度 0.70