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• Unsupervised Machine Learning and Beyond Machine Learning
  crossref Keisuke Takahashi, Lauren Takahashi 2024-03-30T07:01:42Z 置信度 0.70
• OVERVIEW: MACHINE LEARNING
  Machine learning is a subfield of artificial intelligence that involves the development of algorithms that allow computers to learn from data, without being explicitly programmed. It involves the use of statistical models and algorithms to analyse and identify…
  crossref Vaishali Jain, Shiv Kumar Tiwari 2024-05-07T02:15:51Z 置信度 0.70
• Machine Learning and Cybersecurity
  crossref Tony Thomas, Athira P. Vijayaraghavan, Sabu Emmanuel 2019-12-16T17:02:52Z 置信度 0.70
• The Robustness of the p-Norm Algorithms
  crossref Claudio Gentile 2003-11-03T19:30:08Z 置信度 0.70
• Artificial Intelligence and Machine Learning
  Artificial intelligence and machine learning have always been hot topics in news and science fiction. Recently they got more media attention because of technology breakthroughs in deep learning and more consumer-facing applications on the market. The terms mac…
  crossref Shing Lyu 2020-02-27T11:02:38Z 置信度 0.70
• A Comparative Study of Machine Learning and Deep Learning Techniques for Cardiovascular Disease Prediction Using Clinical Health Records
  Cardiovascular disease (CVD) remains the leading cause of global death, highlighting the need for effective and early detection methods. We introduce a comparative study of machine learning (ML) and deep learning (DL) algorithms for the prediction of cardiovas…
  crossref Deep Dave, Madhu Shukla, Neel Dholakia, Vipul Ladva 2025-11-17T18:38:53Z 置信度 0.70
• Supplemental Information 3: Light Gradient Boosting Machine code snippets used during machine learning analysis
  crossref 2025-03-05T03:05:31Z 置信度 0.70
• Psychiatric comorbid disorders of cognition: A machine learning approach using 1,175 UK Biobank participants
  Abstract Background Conceptualising comorbidity is complex and the term is used variously. Here, it is the coexistence of two or more diagnoses which might be defined as ‘chronic’ and, although they may be pathologically related, they may also act independentl…
  crossref Chenlu Li, Delia A. Gheorghe, John E.J. Gallacher, Sarah Bauermeister 2019-09-27T14:05:14Z 置信度 0.70
• Project management for a machine learning project
  crossref Peter Dabrowski 2021-01-30T01:43:45Z 置信度 0.70
• Machine Learning in the Construction of Library's Special Collection Document Information Resources
  With the rapid development of Internet technology, more and more people begin to focus on the construction of library (CL) information resources (IR) in the field of mobile network and social media applications.In order not to let the unique culture disappear …
  crossref 2023-02-06T02:56:36Z 置信度 0.70
• Tuning and Adjusting
  We’ve talked about several mechanisms in this book for looking back and reflecting on past progress with an aim to becoming more effective as individuals, managers, and teams. To recap those mechanisms, they include Retrospectives , Data Wallows, Quality Revie…
  crossref Eric Carter, Matthew Hurst 2019-08-21T15:03:53Z 置信度 0.70
• Research Note on Decision Lists
  crossref Ron Kohavi, Scott Benson 2003-04-04T16:55:36Z 置信度 0.70
• Classification of Cancerous Profiles Using Machine Learning
  There are a variety of options available for cancer treatment. The type of treatment recommended for an individual is influenced by various factors such as cancer-type, the severity of a cancer (stage) and most important the genetic heterogeneity. In such a co…
  crossref Aman Sharma, Rinkle Rani 2018-03-22T16:25:36Z 置信度 0.70
• Transforming Healthcare through Machine Learning and the Internet of Things
  Machine learning (ML) and the Internet of Things (IoT) are two of the most influential and disruptive technologies in the modern world. They have the potential to transform healthcare by providing innovative solutions that can improve the quality, efficiency, …
  crossref Faridoddin Shariaty 2024-10-02T15:32:01Z 置信度 0.70
• "Precision Dining: Machine Learning Techniques for Intelligent Food Recommendations"
  The rise of personalized services has transformed numerous industries, and the food sector is no exception. This paper delves into the development of a machine learning-based intelligent food recommendation system designed to enhance the dining experience thro…
  crossref Jayashree Paul, Sourav Saha 2026-06-18T11:06:12Z 置信度 0.70
• Machine Learning in Optimising Nursing Care Delivery Models: An Empirical Analysis of Hospital Wards
  ABSTRACT Objective This study aims to assess the performance of machine learning (ML) techniques in optimising nurse staffing and evaluating the appropriateness of nursing care delivery models in hospital wards. The primary outcome measures include the adequac…
  crossref Manar Aslan, Ergin Toros 2025-01-21T08:46:32Z 置信度 0.70
• Deus Ex Machina? Predicting SARS-CoV-2 Infection from Lab Tests Using Machine Learning
  Coronavirus 2019 (COVID-19) has disrupted lives, the economy, and healthcare systems across the globe, unlike any infectious disease in 100 years. As we collectively seek to survive and emerge from this ongoing crisis, it is worth evaluating any scientific dis…
  crossref Christopher R McCudden 2020-10-10T04:29:18Z 置信度 0.70
• From epidemiological models to machine learning in clinical prediction
  crossref Liang-Kung Chen 2026-02-10T16:01:28Z 置信度 0.70
• Ordinal Scaling for Clinical Scores with Inconsistent Intervals (900 Patients)
  crossref Ton J. Cleophas, Aeilko H. Zwinderman 2020-03-03T10:02:54Z 置信度 0.70
• S18.4: Machine learning and micro array data in clinical research
  crossref Berthold Lausen 2004-04-13T12:39:23Z 置信度 0.70
• Machine Learning for Personalized Medicine: Clinical Outcome Prediction and Diagnosis : Plenary Talk
  Machine learning and computational intelligence have been applied to a wide range of medical problems to assist medical professionals in decision-making. Especially artificial neural networks, fuzzy systems and powerful hybrid neuro-fuzzy approaches have alrea…
  crossref Zarko Cojbasic 2020-06-09T21:46:49Z 置信度 0.70
• Faculty Opinions recommendation of Can machine-learning improve cardiovascular risk prediction using routine clinical data?
  crossref Jennifer K Quint 2021-08-11T09:55:11Z 置信度 0.70
• Machine Learning Prediction of Reversible Versus Progressive Cognitive Impairment Using Clinical Documentation (P10-12.014)
  crossref Peter Pressman 2026-06-10T17:56:11Z 置信度 0.70
• Modern Machine Learning Techniques
  This chapter contains sections titled: A Unified Framework for Manifold Learning Spectral Clustering and Graph Cut Ensemble Manifold Learning Multiple Kernel Learning Multiview Subspace Learning Multiview Distance Metric Learning Multi-Task Learning Chapter Su…
  crossref 2013-04-02T17:21:44Z 置信度 0.70
• Writing Machine Learning Code
  Programming is, in many ways, a conversation with a computer, but it is also conversation with other developers [105]. As vague as it sounds, we should strive to write code that is simple to read and whose meaning is obvious [252]. Code is read much more often…
  crossref Marco Scutari, Mauro Malvestio 2023-03-01T17:03:18Z 置信度 0.70
• Monetizing Retail Machine Learning
  In this chapter, I am going to put forward some innovative ideas that can be monetized using machine learning. I will also show you some examples where a similar approach has been used and has succeeded.
  crossref Puneet Mathur 2018-12-12T14:05:50Z 置信度 0.70
• MACHINE LEARNING APPLICATIONS IN SOIL CLASSIFICATION AND CHARACTERIZATION
  Accurate soil classification and characterization form the foundation of agricultural productivity, environmental assessment, and civil engineering design.Conventional soil analysis relies on laboratory testing and empirical correlations, which are often time-…
  crossref Aashi Chandarana 2025-12-02T14:46:03Z 置信度 0.70
• Support Vector Machine
  crossref Hang Li 2023-12-06T00:02:11Z 置信度 0.70
• Artificial neural networks and machine learning in anesthesia and perioperative medicine: Reflections on the 2024 Nobel prize in physics
  crossref Yahui Xu, Nie Zhang 2024-12-26T22:05:17Z 置信度 0.70
• Integrated Clinical, Molecular, and Machine Learning Assessment of Familial Hypercholesterolemia
  Background: In clinical practice, LDL-dominant familial hypercholesterolemia (FH) may overlap phenotypically with triglyceride-dominant or mixed familial dyslipidemia. Rule-based diagnostic approaches like the Dutch Lipid Clinic Network (DLCN) and Simon Broome…
  crossref Mustafa Tarık Alay, Atakan Deniz, Hanife Saat, Haktan Bağış Erdem 2026-04-09T12:21:32Z 置信度 0.70
• CellPhenoX: An eXplainable Cell-specific machine learning method to predict clinical Phenotypes using single-cell multi-omics
  SUMMARY Single-cell technologies have enhanced our knowledge of molecular and cellular heterogeneity underlying disease. As the scale of single-cell datasets expands, linking cell-level phenotypic alterations with clinical outcomes becomes increasingly challen…
  crossref Jade Young, Jun Inamo, Zachary Caterer, Revanth Krishna 等 2025-01-27T20:20:20Z 置信度 0.70
• Explainable and Interpretable Machine Learning Frameworks for Early Diabetes Risk Prediction and Clinical Decision Support
  Early detection of diabetes is essential for preventing severe health complications, improving patient outcomes, and enabling timely medical intervention through personalized healthcare strategies. With the growing availability of healthcare data and advanceme…
  crossref Arvind Kulkarni 2026-08-14T16:23:38Z 置信度 0.70
• Machine Learning-Based Anomaly Detection in Cloud Virtual Machine Resource Usage
  Anomaly detection is an important activity in cloud computing systems because it aids in the identification of odd behaviours or actions that may result in software glitch, security breaches, and performance difficulties. Detecting aberrant resource utilizatio…
  crossref Tarun Mourya Satveli 2023-06-15T15:53:00Z 置信度 0.70
• Prevent Road Accident using Machine to Machine (M2M) Learning
  The number of road casualties is steadily rising, while the age of driverless vehicles on the road is rapidly coming. Machine-to-machine (M2M) communication and the use of Big Data created by M2M communication have enormous promise for improving road safety. A…
  crossref Taibu 2022-07-02T05:26:04Z 置信度 0.70
• Erratum to “Automated recognition of individual performers from de-identified video sequences” [Machine Learning with Applications 11 (2023) 100450]
  crossref Zizui Chen, Stephen Czarnuch, Erica Dove, Arlene Astell 2024-02-07T05:03:21Z 置信度 0.70
• Applications of machine learning and deep learning in precision medicine: Opportunities and challenges in genomics, oncology and clinical integration (Review)
  With the advancement of precision medicine, machine learning (ML) and deep learning have increasingly become a pivotal tool for driving medical innovation. Precision medicine, grounded in individual variability, aims to deliver personalized treatment intervent…
  crossref Qiang Zhao, Guangxin Li, Kunpeng Du 2025-10-15T12:10:54Z 置信度 0.70
• Machine learning metabolomics profiling of dietary interventions
  crossref A. Kouraki, A. Nogal, W. Nocun, P. Louca 等 2024-09-19T07:48:17Z 置信度 0.70
• Identifying Adverse Drug Events in Clinical Text Using Fine-Tuned Clinical Language Models: Machine Learning Study
  Abstract Background Medications are essential for health care but can cause adverse drug events (ADEs), which are harmful and sometimes fatal. Detecting ADEs is a challenging task because they are often not documented in the structured data of electronic healt…
  crossref Elizaveta Kopacheva, Aron Henriksson, Hercules Dalianis, Tora Hammar 等 2025-07-23T04:25:06Z 置信度 0.70
• Do You See What I See? Automated IFE Interpretation Using Machine Learning
  Recent advances in machine learning (ML) have opened the possibility of applying this powerful toolset more broadly to address diagnostic problems in laboratory medicine. The clinical laboratory is a natural area in which to utilize ML, as laboratories routine…
  crossref Stephen R Master, Shannon Haymond 2022-12-28T14:02:29Z 置信度 0.70
• Machine Learning for Clinical Predictive Analytics
  In this chapter, we provide a brief overview of applying machine learning techniques for clinical prediction tasks. We begin with a quick introduction to the concepts of machine learning, and outline some of the most common machine learning algorithms. Next, w…
  crossref Wei-Hung Weng 2020-07-31T14:03:07Z 置信度 0.70
• O-21 Separation of major depression patients from healthy controls using machine learning approach to resting-state EEG
  crossref Alexander Ledovsky, Elena Mnatsakanian, Maxim Sharaev, Evgeny Burnaev 2019-05-29T21:09:00Z 置信度 0.70
• The Influence Machine: Nonnegative Instance-Space Learning with Differentiated Regularization
  We introduce a new method for classification called the influence machine. The influence machine assigns influence powers to the instances in the training sample so that they can apply their influence to other instances through the connections between the inst…
  crossref Jian Zhang 2011-02-03T16:55:42Z 置信度 0.70
• Stock Price Prediction using Machine Learning
  The stock market has long attracted the attention of both researchers and ordinary people. Essentially, a typical person believes that investing in the stock market is akin to catching a falling knife because they believe that there is no way to foresee the pr…
  crossref Anshuman Behera, Ayes Chinmay 2023-03-28T18:02:17Z 置信度 0.70
• iForecast: Machine Learning Time Series Forecasting
  Compute onestep and multistep time series forecasts for machine learning models.
  crossref Ho Tsung-wu 2024-06-12T12:28:15Z 置信度 0.70
• Machine Learning Enables Decision-Making Processes for an Enterprise
  Business decisions need to be made based on constantly changing data from a variety of sources. The data for business enterprises consists of both internal and external sources. Some managerial decisions are qualitative. Thus, it is necessary to incorporate th…
  crossref N. Raghavendra Rao 2023-01-20T15:44:01Z 置信度 0.70
• The (Black Box) Machine Learning Process
  crossref Gerald Friedland 2023-12-01T06:02:58Z 置信度 0.70
• Introducing the Viewpoint in the Resource Description using Machine Learning
  Search engines allow providing the user with data and information according to their interests and specialty. Thus, it is necessary to exploit descriptions of the resources, which take into consideration viewpoints. Generally, the resource descriptions are ava…
  crossref Ouahiba Djama 2021-09-28T11:38:29Z 置信度 0.70
• Introduction to Machine Learning
  crossref Tony Thomas, Athira P. Vijayaraghavan, Sabu Emmanuel 2019-12-16T17:02:52Z 置信度 0.70
• Quantum Machine Learning: An Applied Approach
  This book on adapting quantum computing and machine learning algorithms takes a hands-on approach using updated libraries.
  crossref Santanu Ganguly 2021-07-29T20:04:30Z 置信度 0.70
• The Definitive Guide to Machine Learning Operations in AWS
  This book covers AWS MLOps tools such as Amazon SageMaker, Data Wrangler, and AWS Feature Store, along with best practices for operating ML systems on AWS.
  crossref Neel Sendas, Deepali Rajale 2025-01-03T18:04:13Z 置信度 0.70
• Reinforcement learning (machine learning)
  crossref Frank Gaillard, Andrew Murphy, Jarrel Seah 2021-10-25T01:54:02Z 置信度 0.70
• Ontology Learning
  crossref 2010-12-29T17:26:38Z 置信度 0.70
• Statistical Learning
  crossref 2010-12-29T17:22:42Z 置信度 0.70
• Figure 1: The machine learning pipeline.
  crossref 2024-04-19T03:45:50Z 置信度 0.70
• Quantum Machine Learning
  crossref 2016-08-04T05:30:35Z 置信度 0.70
• Sparsity-Aware Learning
  crossref Sergios Theodoridis 2015-04-10T22:52:56Z 置信度 0.70
• Sparsity-Aware Learning
  crossref Sergios Theodoridis 2015-04-10T22:52:56Z 置信度 0.70
• 223 The Clinical Applications of Machine Learning in Plastic and Reconstructive Surgery: A Systematic Review
  Abstract Background Machine learning (ML) is a set of models and methods that can automatically detect patterns in vast amounts of data and use this information to perform various kinds of decision-making under uncertain conditions. The aim of this review is t…
  crossref A Mantelakis 2021-05-08T15:00:20Z 置信度 0.70
• Accessing artificial intelligence and machine learning for clinical decision making
  crossref S. Sawant, A.R. Bhatia, S.V. Arya 2024-05-08T06:52:40Z 置信度 0.70
• Clinical Decision Support System Using a Machine Learning Model to Assist Simultaneous Cardiopulmonary Auscultation: Open-Label Randomized Controlled Trial
  crossref Takanobu Hirosawa, Tetsu Sakamoto, Yukinori Harada, Taro Shimizu 2023-06-15T19:11:57Z 置信度 0.70
• Feasibility Study: Machine Learning in Neurodegenerative Disorders, Alzheimer’s Disease
  Introduction: Clinical decision support systems (CDSSs), powered by machine learning and artificial intelligence, have demonstrated potential in clinical diagnosis and intervention for neurological and psychiatric disorders. Considering the importance of early…
  crossref Xiangxuan Kong 2023-02-03T05:16:12Z 置信度 0.70
• ENHANCED COPD RISK PREDICTION USING CLINICAL DATA: A MACHINE LEARNING-BASED COPD-RINET FRAMEWORK
  Chronic Obstructive Pulmonary Disease (COPD) is a long-term lung disease that makes normal breathing more difficult as it develops, often underdiagnosed in its early stages, particularly in settings lacking spirometry. This study presents COPD-RiNet, a machine…
  crossref C. Maheswari 2026-01-31T09:18:56Z 置信度 0.70
• Semantic and phonetic markers in schizophrenia-spectrum disorders; a combinatory machine learning approach
  Abstract Introduction Speech is a promising marker for schizophrenia-spectrum disorder diagnosis, as it closely reflects symptoms. Previous approaches have made use of different feature domains of speech in classification, including semantic and phonetic featu…
  crossref A.E. Voppel, J.N. de Boer, S.G. Brederoo, H.G. Schnack 等 2022-07-15T15:50:18Z 置信度 0.70
• EARLY DETECTION OF PANCREATIC CANCER USING URINARY BIOMARKERS AND CLINICAL FEATURES: A BIOSTATISTICAL AND MACHINE LEARNING APPROACH
  crossref 2025-12-30T09:49:51Z 置信度 0.70
• Machine Learning-Based Prediction of COVID-19 Patient Outcomes: Enhancing Clinical Decision-Making
  The COVID-19 epidemic has created unprecedented challenges to healthcare systems around the world, demanding the development of reliable techniques for predicting patient outcomes to guide clinical decisions. This paper comprehensively explores machine learnin…
  crossref Nitin N. Sakhare 2024-11-15T09:00:13Z 置信度 0.70
• AI-Driven Quality Assurance Frameworks for Decentralized Clinical Trials
  Traditional quality assurance (QA) processes used in electronic Clinical Outcome Assessment (eCOA), and Decentralized Clinical Trial (DCT) platforms rely on a variety of manual, reactive approaches with many regulatory risk elements. The purpose of this resear…
  crossref Rohit Singh Raja 2026-01-08T07:17:34Z 置信度 0.70
• Eye-tracking biomarkers of clinical expertise in ECG interpretation: statistical and machine learning evidence
  Introduction Interpreting the electrocardiogram (ECG) is a fundamental clinical skill, and mistakes are still prevalent in the workforce, especially among trainees and non-specialist clinicians. Eye-tracking technology has recently become a popular method for …
  crossref Eyad Talal Attar 2026-02-13T14:36:35Z 置信度 0.70
• Bridging the Gap Between Machine Learning Innovation and Clinical Practice
  crossref Salvatore Pepe 2026-05-08T01:15:24Z 置信度 0.70
• Why Operationalizing Machine Learning Requires a Shrewd Business Perspective
  crossref 2019-12-18T21:01:21Z 置信度 0.70
• Pneumonia Detection Using Machine Learning and Deep Learning Methods on Clinical and Chest X-Ray Data
  Pneumonia remains a major global health problem requiring timely and accurate treatment to improve patient outcomes. This study presents a comparative analysis of machine learning and deep learning methods for pneumonia detection using both clinical and chest …
  crossref Athira V. P. 2025-10-25T07:17:07Z 置信度 0.70
• Continual Learning
  crossref 2010-12-29T17:42:10Z 置信度 0.70
• Offline Learning
  crossref 2010-12-29T17:26:38Z 置信度 0.70
• Passive Learning
  crossref 2010-12-29T17:26:04Z 置信度 0.70
• Incremental extreme learning machine
  I-ELM and other Popular Incremental Learning Algorithms . . . . .
  crossref Lei Chen 2019-10-02T15:11:06Z 置信度 0.70
• Machine Learning for Biosensors
  Biosensors have become increasingly popular as diagnostic tools due to their ability to detect and quantify biological analytes in a wide range of applications. With the growing demand for faster and more reliable biosensing devices, machine learning has becom…
  crossref Gayathri Anapanani 2023-08-14T15:31:44Z 置信度 0.70
• A Machine Learning Study of 534,023 Medicare Beneficiaries with COVID-19: Implications for Personalized Risk Prediction for People Over 65
  The global outbreak of COVID-19 has resulted in over 378 million infections and worldwide casualties have surpassed 5.6 million. Identifying individuals at highest risk of COVID-19 death may help risk evaluation and health service provision. Personalized risk …
  crossref 2022-09-16T16:36:23Z 置信度 0.70
• Additional file 1 of Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis
  Supplementary Materials 1.
  datacite Amiri, Hamidreza, Peiravi, Samira, rezazadeh shojaee, Seyedeh sara, Rouhparvarzamin, Motahareh 等 2024 置信度 0.66 Biological Sciences not elsewhere classifiedScience Policy
• Additional file 1 of Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis
  Supplementary Materials 1.
  datacite Amiri, Hamidreza, Peiravi, Samira, rezazadeh shojaee, Seyedeh sara, Rouhparvarzamin, Motahareh 等 2024 置信度 0.66 Biological Sciences not elsewhere classifiedScience Policy
• Artificial Intelligence Jammalamudi Chaitanya babu and Machine Learning in Healthcare: A Comprehensive Review of Clinical Applications, Challenges, And Future Perspectives
  The integration of artificial intelligence (AI) and machine learning (ML) technologies in healthcare has revolutionized clinical decision-making, diagnostic accuracy, and treatment planning. This comprehensive review examines the current state of AI/ML applica…
  datacite Jammalamudi Chaitanya babu, Dr. Jayant Isaac 2026 置信度 0.66
• Artificial Intelligence Jammalamudi Chaitanya babu and Machine Learning in Healthcare: A Comprehensive Review of Clinical Applications, Challenges, And Future Perspectives
  The integration of artificial intelligence (AI) and machine learning (ML) technologies in healthcare has revolutionized clinical decision-making, diagnostic accuracy, and treatment planning. This comprehensive review examines the current state of AI/ML applica…
  datacite Jammalamudi Chaitanya babu, Dr. Jayant Isaac 2026 置信度 0.66
• AI-Induced Intelligence Erosion and Susceptibility to AI Hallucinations in Health Professions Education: A scoping review protocol
  This scoping review will systematically map evidence on the relationship between AI-induced intelligence erosion (including automation bias, cognitive offloading, and reduced critical thinking) and health professions students' ability to detect AI hallucinatio…
  datacite Karna, Swarnim Lal, Khadka, Anjan 2026 置信度 0.66 Physical Sciences and MathematicsMedicine and Health SciencesEducationComputer SciencesArtificial Intelligence and Robotics
• COVID-19: A Global Biological Update Beyond Viral Pathogen Narratives, Functioning as a High-Dimensional Respiratory Sync to Align Human DNA with Earth's New Frequency and Execute a Complete Structural Reconstruction of Global Genetic Architecture.
  COVID-19: A Global Biological Update Beyond Viral Pathogen Narratives, Functioning as a High-Dimensional Respiratory Sync to Align Human DNA with Earth’s New Frequency and Execute a Complete Structural Reconstruction of Global Genetic Architecture ............…
  datacite JALALI, SEYED RASOUL 2026 置信度 0.66
• COVID-19: A Global Biological Update Beyond Viral Pathogen Narratives, Functioning as a High-Dimensional Respiratory Sync to Align Human DNA with Earth's New Frequency and Execute a Complete Structural Reconstruction of Global Genetic Architecture.
  COVID-19: A Global Biological Update Beyond Viral Pathogen Narratives, Functioning as a High-Dimensional Respiratory Sync to Align Human DNA with Earth’s New Frequency and Execute a Complete Structural Reconstruction of Global Genetic Architecture ............…
  datacite JALALI, SEYED RASOUL 2026 置信度 0.66
• COVID-19: A Global Biological Update Beyond Viral Pathogen Narratives, Functioning as a High-Dimensional Respiratory Sync to Align Human DNA with Earth's New Frequency and Execute a Complete Structural Reconstruction of Global Genetic Architecture.
  COVID-19: A Global Biological Update Beyond Viral Pathogen Narratives, Functioning as a High-Dimensional Respiratory Sync to Align Human DNA with Earth’s New Frequency and Execute a Complete Structural Reconstruction of Global Genetic Architecture ............…
  datacite JALALI, SEYED RASOUL 2026 置信度 0.66
• Rational Use of Antibiotics in the Era of Antimicrobial Resistance: Recent Advances and Future Directions
  Antimicrobial resistance (AMR) represents a critical global public health threat, undermining a century of medical advancement and posing significant risks to modern healthcare systems. The irrational and excessive application of antibiotics in human and anima…
  datacite Mudhalkar Karan, Kotgire Omkar, Dr. Giri Ashok Bhimrao 2026 置信度 0.66 Antimicrobial resistance, rational use of antibiotics, antimicrobial stewardship, rapid diagnostics, One Health, antibiotic policy.
• Rational Use of Antibiotics in the Era of Antimicrobial Resistance: Recent Advances and Future Directions
  Antimicrobial resistance (AMR) represents a critical global public health threat, undermining a century of medical advancement and posing significant risks to modern healthcare systems. The irrational and excessive application of antibiotics in human and anima…
  datacite Mudhalkar Karan, Kotgire Omkar, Dr. Giri Ashok Bhimrao 2026 置信度 0.66 Antimicrobial resistance, rational use of antibiotics, antimicrobial stewardship, rapid diagnostics, One Health, antibiotic policy.
• Human Factors & Just Culture in Paramedicine | Work-as-Done vs Work-as-Imagined (Ivan McCann)
  Episode Summary In this episode, Ivan McCann joins the podcast to discuss human factors, patient safety, and just culture in paramedicine. With experience spanning Ontario EMS, remote and austere medical environments, and Ireland’s community healthcare system,…
  datacite Cichowski, RYAN, Rodger, Jakob, McCann, Ivan 2026 置信度 0.66
• Human Factors & Just Culture in Paramedicine | Work-as-Done vs Work-as-Imagined (Ivan McCann)
  Episode Summary In this episode, Ivan McCann joins the podcast to discuss human factors, patient safety, and just culture in paramedicine. With experience spanning Ontario EMS, remote and austere medical environments, and Ireland’s community healthcare system,…
  datacite Cichowski, RYAN, Rodger, Jakob, McCann, Ivan 2026 置信度 0.66
• Perceived Impact of Artificial Intelligence Usage on Academic Performance Among Undergraduate Health Science Students in Mirpurkhas, Sindh-Pakistan: A Multi-Center Study
  Background: Many medical and nursing students are increasingly utilizing artificial intelligence tools such as Telemedicine, Jeni.AI, Gemini, and ChatGPT to support both academic and clinical activities. These tools offer rapid responses and can save valuable …
  datacite Samia Khalil Ahmed, Irfan Ali Chandio, Anum Pervaiz, Aiman Fatima 等 2025 置信度 0.66 Artificial IntelligenceHealthcare EducationAcademic PerformanceUndergraduate StudentsPerception; Mirpurkhas
• Perceived Impact of Artificial Intelligence Usage on Academic Performance Among Undergraduate Health Science Students in Mirpurkhas, Sindh-Pakistan: A Multi-Center Study
  Background: Many medical and nursing students are increasingly utilizing artificial intelligence tools such as Telemedicine, Jeni.AI, Gemini, and ChatGPT to support both academic and clinical activities. These tools offer rapid responses and can save valuable …
  datacite Samia Khalil Ahmed, Irfan Ali Chandio, Anum Pervaiz, Aiman Fatima 等 2025 置信度 0.66 Artificial IntelligenceHealthcare EducationAcademic PerformanceUndergraduate StudentsPerception; Mirpurkhas
• Performance and Applicability of ChatGPT and Other Generative Artificial Intelligence on Hypertension: A Scoping Review
  This scoping review aims to map and synthesize the existing evidence on the performance and applicability of ChatGPT and other generative artificial intelligence (AI) tools in the context of hypertension. The review will examine how generative AI has been used…
  datacite GC, Saroj, Dheeraj Kumar Maheshwari, Bhusal, Pawan, Basnet, Bibhusan 等 2026 置信度 0.66 Physical Sciences and MathematicsCardiologyMedicine and Health SciencesMedical SpecialtiesComputer Sciences
• An audit of AI-related documents across U.S. medical schools: A framework-based qualitative content analysis
  Medical schools would benefit from systematic guidance for developing comprehensive artificial intelligence (AI) policies, given generative AI’s rapid integration into medical education. This study developed and applied an idealized AI policy framework to anal…
  datacite Rush, Emily, Byram, Jessica N., Garnett, Colleen N., DeVaul, Nicole 等 2025 置信度 0.66 MedicineGeneticsFOS: Biological sciencesSociologyFOS: Sociology
• An audit of AI-related documents across U.S. medical schools: A framework-based qualitative content analysis
  Medical schools would benefit from systematic guidance for developing comprehensive artificial intelligence (AI) policies, given generative AI’s rapid integration into medical education. This study developed and applied an idealized AI policy framework to anal…
  datacite Rush, Emily, Byram, Jessica N., Garnett, Colleen N., DeVaul, Nicole 等 2025 置信度 0.66 MedicineGeneticsFOS: Biological sciencesSociologyFOS: Sociology
• Mapping AI-augmented computing architectures for IoT-based fall prevention in older adults: a scoping review
  This scoping review aims to systematically map and synthesize the existing literature on AI-augmented computing architectures — including edge, fog, cloud, and hybrid configurations — applied to Internet of Health Things (IoHT)-based fall prevention systems fo…
  datacite DHARMANSYAH, DHIKA 2026 置信度 0.66 Health Information TechnologyPhysical Sciences and MathematicsGeriatricsPublic HealthMedicine and Health Sciences
• MH 370 Exact Location. (Broken Ridge and a Depth of 4,648.35 Meters in the Southern Indian Ocean, at Coordinates Longitude 93.6165° E and Latitude 34.4812° S).(3428S-9336E).
  MH370 Related Research Papers: MH370: Mathematical Proof of the Survival of All Passengers Within a Tensorial Capsule at Broken Ridge and a Depth of 4,648.35 Meters in the Southern Indian Ocean, at Coordinates Longitude 93.6165° E and Latitude 34.4812° S (3428…
  datacite JALALI, SEYED RASOUL 2026 置信度 0.66
• MH 370 Exact Location. (Broken Ridge and a Depth of 4,648.35 Meters in the Southern Indian Ocean, at Coordinates Longitude 93.6165° E and Latitude 34.4812° S).(3428S-9336E).
  MH370 Related Research Papers: MH370: Mathematical Proof of the Survival of All Passengers Within a Tensorial Capsule at Broken Ridge and a Depth of 4,648.35 Meters in the Southern Indian Ocean, at Coordinates Longitude 93.6165° E and Latitude 34.4812° S (3428…
  datacite JALALI, SEYED RASOUL 2026 置信度 0.66
• Energy Sustainability Strategies in the Implementation of Generative AI in Healthcare: A Scoping Review
  This project aims to map and synthesize the strategies and patterns related to energy sustainability in the implementation and use of generative artificial intelligence (AI) in healthcare settings. The rapid adoption of large language models (LLMs) and other g…
  datacite Flach, Julia Camilly Assunção, Schiavon, Dieine Estela Bernieri 2026 置信度 0.66 SustainabilityPhysical Sciences and MathematicsMedicine and Health SciencesEnvironmental SciencesComputer Sciences
• Exploring Artificial Intelligence Models for the Diagnosis of Sarcopenia: A Scoping Review
  Objetive: The objective of this scoping review is to systematically map the existing literature on AI and ML models developed for the detection or prediction of sarcopenia, to describe their methodological characteristics, input features, model performance, va…
  datacite Loyola, Walter Aquiles Sepúlveda, Barros-Osorio, Cristián, Gallegos, Eduardo 2026 置信度 0.66 Medicine and Health SciencesLife Sciencesartificial intelligencemachine learningsarcopenia
• Advances in Diagnostic Technologies and Precision Medicine: Clinical Anatomy–Oriented Insights from WHX Labs 2026
  Recent advances in diagnostic technologies and precision medicine have transformed clinical decision-making, emphasizing individualized patient care based on biological, molecular, and anatomical variability. Clinical anatomy remains a foundational pillar in t…
  datacite Dr. Uma Pandalai 2026 置信度 0.66 Clinical anatomy; diagnostic technologies; precision medicine; WHX Labs 2026; biomedical innovation; imaging diagnostics
• Advances in Diagnostic Technologies and Precision Medicine: Clinical Anatomy–Oriented Insights from WHX Labs 2026
  Recent advances in diagnostic technologies and precision medicine have transformed clinical decision-making, emphasizing individualized patient care based on biological, molecular, and anatomical variability. Clinical anatomy remains a foundational pillar in t…
  datacite Dr. Uma Pandalai 2026 置信度 0.66 Clinical anatomy; diagnostic technologies; precision medicine; WHX Labs 2026; biomedical innovation; imaging diagnostics