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• Distributed IoT Security with Blockchain, Privacy-Preserving Techniques, and Predictive Maintenance Models
  europepmc 2026 置信度 0.80
• A deep-learning based gait classification and anomaly detection framework for healthcare surveillance.
  Gait classification and anomaly detection are non-intrusive approaches that can support healthcare surveillance and clinical gait analysis by identifying abnormal walking patterns. Despite recent advancements, existing methods remain limited by model complexit…
  pubmed Alfridi MF 2026 置信度 0.82
• Robust Personalized Federated Continual Learning via Explainable Multi-Granularity Prompt.
  Personalized Federated Continual Learning (PFCL) requires that the server not only effectively integrate temporal knowledge accumulated across past tasks and spatial knowledge distributed among heterogeneous clients, but also ensure strong personalized perform…
  pubmed Yu H, Yang X, Fan B, Li Y 等 2026 置信度 0.82
• An Empirical Study of Stability and Fairness Side-Effects of Federated Unlearning for Departed Clients under Non-IID Data
  europepmc 2026 置信度 0.80
• Federating European REgistries for Stroke: Principles, Data Model and Future Perspectives for a Federated Analysis of Multiple Prospective Stroke Registries.
  Acute ischemic stroke is a leading cause of death and disability. Despite strong evidence supporting reperfusion therapies and Stroke Unit care, access and quality of stroke services remain heterogeneous across Europe. Although national stroke registries provi…
  pubmed Salerno A, Melissargos G, Katan M, Knoflach M 等 2026 置信度 0.82
• A Privacy-Preserving Federated Intrusion Detection Framework with Reputation-Aware Client Selection and Integrity Verification
  europepmc 2026 置信度 0.80
• HARMONY: Hybrid Aggregation and Reputation Mechanism for Cooperative Federated Survival Analysis.
  Federated Learning (FL) holds promise for digital health by enabling collaborative model training without compromising patient data privacy. However, differences in data completeness, censoring rates, patient populations, institutional reliability, and contrib…
  pubmed Seidi N, Roy S, Das S 2026 置信度 0.82
• Federated Deep Learning-Based Robust Sparse System Identification Using Correntropy and Sparsity-Aware Optimization
  europepmc 2026 置信度 0.80
• Putting the human at the core of human-in-the-loop optimization: integrating clinical expertise and human capacities in exoskeleton learning. An interdisciplinary perspective paper.
  This interdisciplinary perspective aims to identify key limitations in current Human-in-the-Loop Optimization (HILO) approaches for lower-limb exoskeletons (LLEs) and to propose a shift toward more human-centred optimization.
  pubmed Beckwée D, Filtjens B, Claeys R, Lambranzi C 等 2026 Aug 27 置信度 0.82
• Stage-Aware Swin-Enhanced nnU-Net v2 for Robust Polyp Segmentation in Collaborative Endoscopic Visual Sensing.
  Automatic colon polyp segmentation is important for reliable endoscopic visual sensing. However, segmentation performance can be degraded by ambiguous lesion boundaries, heterogeneous appearance, and image quality variations during acquisition or transmission.…
  pubmed Bai Y, Liu H 2026 Aug 17 置信度 0.82
• Artificial Intelligence and Digital Pathology: Technological Transformation and Strategic Impact in Clinical Research and Medical Affairs.
  The progressive integration of Whole Slide Imaging (WSI) technology and Artificial Intelligence (AI) architectures is driving a structural transformation in pathology and precision oncology. This structured critical review analyzes and systematizes the impact …
  pubmed Baviello C, Capuano DM, Verna R 2026 Aug 16 置信度 0.82
• Artificial Intelligence in Xenotransplantation: A Prioritized Roadmap for Early Clinical Translation, Opportunities and Challenges.
  Xenotransplantation represents a potential solution to the persistent global organ shortage, yet its clinical application remains stalled by complex immunologic responses, coagulation dysregulation, species-specific biology, and infectious risks. Artificial in…
  pubmed Shirini K, Hahn Z, Ladowski JM, Schulick A 等 2026 Sep-Oct 置信度 0.82
• Current State and Impact of Implementation of In-Silico Tools in the Biopharmaceutical Industry - Proceedings of the 6th Modeling Workshop.
  The sixth modeling workshop (6MW) was held in June 2025 at Collegeville, Pennsylvania, USA, and supported by the Recovery of Biological Products Conference Series. The goal of the workshop was to assemble modeling practitioners to review and discuss the curren…
  pubmed Dumetz A, Staby A, Gerberich C, Roush D 等 2026 Aug 24 置信度 0.82
• Validation of federated analytics across secure data environments: A comparative study of synthetic healthcare datasets using machine learning and general linear models.
  To enable research and innovation, most health data systems are moving away from a model of pooled data egress and instead highlight the benefits of federated analytics to support data analysis across different settings. This study aimed to assess whether the …
  pubmed Gallier S, Topham A, Hodson J, McNulty D 等 2026 Jan-Dec 置信度 0.82
• Local Deployment of Open-Weight Language Models in Dermatology: Viewpoint on Privacy, Equity, and Practical Implementation.
  Generative AI, particularly large language models (LLMs), is reshaping clinical workflows in dermatology. However, cloud-based commercial models pose persistent challenges to Health Insurance Portability and Accountability Act (HIPAA) compliance, especially in…
  pubmed Nahm WJ, Yin ES, Milam EC, Weed JG 2026 Aug 21 置信度 0.82
• Preserving privacy, enabling collaboration: Decentralized learning framework for multi-class orthopedic imaging.
  Medical imaging data are inherently distributed across healthcare institutions and subject to strict privacy regulations, limiting the feasibility of centralized model training. In orthopedic imaging, further challenges arise from heterogeneous diagnostic task…
  pubmed Alwzwazy HA, Gu A, Dukhan M, Zhao Z 等 2026 Aug 19 置信度 0.82
• Utilizing routinely acquired clinical neuroimaging and electronic health record data to advance precision medicine in dementia care.
  Alzheimer's disease (AD) exhibits significant clinical variability in symptom onset, progression rates, neuropsychiatric symptoms and treatment responses. This variability reflects a range of underlying biological, genetic and environmental factors. This revie…
  pubmed Oishi K, Adams R, Nowrangi MA, Zandi PP 等 2026 Aug 19 置信度 0.82
• Enhancing security and efficiency in healthcare cloud computing with blockchain integration and LZW compression: The BICCM framework.
  Modern healthcare system produces large amount of sensitive clinical data, but no existing framework simultaneously addresses and satisfy rigorous security guarantees, storage efficiency and the throughput demand of clinical operations/transactions. All existi…
  pubmed Ullah F, Uddin Z, Sardaraz M, Javed M 等 2026 Aug 19 置信度 0.82
• Recommendations for a national electronic health record in Spain: a Delphi study.
  Despite decades of health-care digitalisation efforts worldwide, health information systems remain highly fragmented, with multiple vendor-specific silos that communicate through incomplete solutions. This fragmentation prevents the creation of real-time, life…
  pubmed Piera-Jiménez J, Cano I, Carot-Sans G, Cresswell K 等 2026 Aug 19 置信度 0.82
• From molecules to minds: Integrative multi-omics in psychiatry.
  Psychiatric disorders are biologically complex conditions arising from interactions across genomic, epigenomic, transcriptomic, proteomic, metabolomic, and metagenomic layers. Single-omics approaches rarely capture more than a fraction of the variance in compl…
  pubmed Abbasi H, Hawn SE, Javanbakht A, Seedat S 等 2026 Sep 置信度 0.82
• DAQSyn: A decentralized adaptive quantization-aware synchronous framework in heterogeneous on-device AI networks.
  Decentralized Federated Learning (DFL) has emerged as a key paradigm for collaborative model training across distributed edge devices while preserving data privacy and system autonomy. However, the performance of existing DFL frameworks is constrained by synch…
  pubmed Bibi M, Khan QW, Yazdan SA, Ahmad R 等 2026 Aug 5 置信度 0.82
• A systematic review of heterogeneity in clinical trial design for anal cancer radiotherapy-immunotherapy combinations.
  Localised anal squamous cell carcinoma (ASCC) is treated with radical chemoradiotherapy, which achieves durable disease control in most patients. However, treatment failure is stage-dependent, with approximately 25-30% of patients with locally advanced disease…
  pubmed Samuel RJ, Samson A, Gilbert DC, Adams R 等 2026 Nov 置信度 0.82
• From pixels to precision: a narrative review of AI-driven 3D morphological analysis and digital twinning in alveolar cleft management.
  Alveolar cleft is a congenital craniofacial anomaly of common occurrence and is frequently seen in cleft lip and palate patients. This condition affects the patient's chewing, speech, and psychological and social life. This review aims to offer a broad overvie…
  pubmed Yang Z, Qian H, Zeng Y, Huang Q 2026 Jul 31 置信度 0.82
• Converge Faster, Talk Less: Hessian-Informed Federated Zeroth-Order Optimization.
  Zeroth-order (ZO) optimization enables dimension-free communication in federated learning (FL), making it attractive for fine-tuning of large language models (LLMs) due to significant communication savings. However, existing ZO-FL methods largely overlook curv…
  pubmed Li Z, Ying B, Liu Z, Dong C 等 2026 置信度 0.82
• Multimodal natural language processing in ophthalmology: bridging clinical text and medical imaging.
  Multimodal natural language processing (NLP) represents a transformative approach in ophthalmology by bridging clinical text and medical imaging to enhance diagnostic accuracy, workflow efficiency, and patient-centered care. The mainstream NLP technologies wer…
  pubmed Qin S, Zhao N, Shen L, Zhang Y 等 2026 置信度 0.82
• Predictive Models for Toxicities after CAR T-cell Therapy: Challenges and Opportunities.
  Chimeric antigen receptor (CAR) T-cell therapy is increasingly utilized with expanding indications beyond hematologic malignancies. Here, we review existing models developed for predicting toxicities in the CAR T-cell setting and identify both strengths and ch…
  pubmed Ma J, Culbert A, Chang TG, Solter ML 等 2026 Aug 11 置信度 0.82
• Image Style Transfer-Empowered Federated Domain Generalization.
  As a distributed machine learning paradigm, federated learning enables collaborative training among multiple clients while preserving data privacy. However, in practical applications, it faces the challenge of domain shift caused by data heterogeneity, which l…
  pubmed Wang Q, Li Q, Li X, Chen S 2026 置信度 0.82
• Multi-modal AI-enabled steatotic liver disease diagnostics using facial images and metabolomics.
  Steatotic liver disease (SLD) affects one-third of the global population, yet current non-invasive diagnostic methods are too costly or operator-dependent for population-scale screening. Here, we present 3D-FAICE, a deep learning system that uses three-dimensi…
  pubmed Gao Y, Wang K, Ke Y, Zou Z 等 2026 Aug 18 置信度 0.82
• Neural-network-inspired federated coordination for noise-tolerant distributed optimization in cyber-physical demand-side management.
  This study proposes a neural-network-inspired computational framework for hierarchical, noise-tolerant coordination in distributed agent networks. The framework is evaluated in a cyber-physical demand-side management testbed in which autonomous home energy man…
  pubmed Gharbi A, Alshammari A, Albalawi N, Ben Halima N 2026 置信度 0.82
• [Research progress on predictive modeling of invasive candidiasis in critically ill patients].
  Invasive candidiasis is one of the common invasive fungal infections in the intensive care unit (ICU), characterized by high incidence, high mortality, and diagnostic difficulty. The clinical presentation of invasive candidiasis lacks specificity, and conventi…
  pubmed Li M, Meng S, Li X, Li S 2026 Jul 置信度 0.82
• From graph models to intelligent decision-making: a review of spatio-temporal graph neural networks for regional disease risk prediction and etiology mining.
  Regional disease risk prediction is a core component of public health early warning systems. Traditional statistical models and machine learning methods have inherent limitations in handling multi-source heterogeneous data fusion, complex spatio-temporal depen…
  pubmed Chen Y, Qin X, Chen S 2026 置信度 0.82
• A federal learning-driven artificial intelligence framework for fundus image myopia diagnosis.
  Myopia has emerged as a critical global public health challenge. This study aims to develop a privacy-preserving federated learning (FL) framework for the triple classification of fundus images (normal, myopia, and pathological myopia), designed to generalize …
  pubmed Yin X, Yu C, Xiong W, Liao Y 2026 Jan-Dec 置信度 0.82
• Artificial intelligence in the early diagnosis of prostate cancer: from multimodal imaging to liquid biopsy.
  Prostate cancer (PCa) is the most prevalent malignant tumor in the urogenital system among men worldwide. Due to its subtle early symptoms and strong tumor heterogeneity, traditional diagnostic methods relying on a single prostate-specific antigen (PSA) initia…
  pubmed Xie J, Yin Z, Gao R, Qiu Z 等 2026 置信度 0.82
• Risk of Pediatric Eye Disease in Children with Neurodevelopmental and Behavioral Disorders in the United States.
  To evaluate the association of neurodevelopmental disorders (NDDs) and behavioral disorders with amblyopia, myopia, strabismus, and strabismus surgery rates.
  pubmed Shah J, Pathuri S, Ong J, Plotnik J 等 2026 Aug 5 置信度 0.82
• Building a Global Research Network for Fair, Accountable, Interpretable, and Responsible AI in Emergency Care: Protocol for a FAIR-EC Study.
  The current landscape of emergency care (EC) is marked by high demand, leading to issues such as emergency department boarding, overcrowding, and subsequent delays that impact the quality and safety of patient care. Integrating data science into EC can enhance…
  pubmed Hong C, Liew JCK, Yu J, Barry T 等 2026 Aug 4 置信度 0.82
• Artificial intelligence in dermatology: A literature review of current evidence and clinical implementation.
  Artificial intelligence is emerging as a transformative and rapidly developing technology, with growing implications for the healthcare sector, including dermatology. We conducted a literature review using PubMed and EMBASE. Included studies primarily focused …
  pubmed Christensen JMM, Nyheim-Tømmerås M, Hansen BK, Haulrig MB 等 2026 Sep 置信度 0.82
• AI-Driven Optimization of Kidney Allocation: Enhancing Precision in Donor-Recipient Matching.
  The growing demand for kidney transplant amid persistent organ scarcity demands improved donor -recipient compatibility assessment. Traditional allocation systems relying on rigid scoring fail to capture complex multidimensional data affecting posttransplant o…
  pubmed Okhovvat M, Amirkhanlou S, Simforoosh N, Poor-Reza Gholi F 等 2026 Jul 置信度 0.82
• Pseudo-Global Based Sequential Contribution Estimation for Federated Semi-Supervised Medical Image Segmentation.
  Federated semi-supervised learning (FSSL) for medical image segmentation has been extensively studied in recent years. Due to the requirement of specialized knowledge and equipment for annotating medical data, only a very limited number of medical institutions…
  pubmed Zhou G, Xu Z, Li B, Zhang Y 等 2026 Jul 28 置信度 0.82
• From Sensor-Empowered Ubiquitous Computing to Embodied Intelligence: Architectures, Paradigm Evolution, and Emerging Challenges.
  With the rapid development of artificial intelligence technology, the transportation, industry, and healthcare fields are undergoing an intelligent evolution. These advancements have raised higher requirements for technologies such as mobile robots, wearable i…
  pubmed Jia A, Cai Z, Liu X, Zheng K 等 2026 Jul 9 置信度 0.82
• Application of Machine Learning for Mean Glandular Dose Prediction Utilizing DICOM Mammography Images.
  The growing demand for raw and processed scientific data has encouraged many researchers and research institutions to adopt an open-source data policy. At present, data accessibility is of paramount importance due to the growing demand for artificial intellige…
  pubmed Alghamdi AAA 2026 Jul 21 置信度 0.82
• Wearable Devices and Machine Learning in Cardiovascular Monitoring: Current Evidence and Future Directions for Precision Medicine.
  Cardiovascular disease remains the leading global health challenge, claiming approximately 19.8 million lives annually. The convergence of wearable technology and artificial intelligence represents a transformative shift in cardiovascular healthcare, enabling …
  pubmed Osonuga A, Dave M, Ogieuhi IJ, Olawade DB 等 2026 Jul 14 置信度 0.82
• The transformative potential of artificial intelligence in pediatric medicine: Current applications, methodological challenges, and future directions.
  Artificial intelligence (AI) possesses the transformative potential to reshape pediatric medicine, offering powerful tools for diagnosis, prognosis, and personalized therapy. This review focuses on three domains selected for their relative maturity in AI devel…
  pubmed Wang R, Ding X, Zhang W, Shi T 2026 Aug 置信度 0.82
• Backspin: A backdoor attack framework for split learning based on smashed data.
  Split Learning (SL) represents a novel collaborative machine learning paradigm tailored for participants with private data and constrained computational capabilities. As with Federated Learning (FL) and other collaborative learning paradigms, SL is also vulner…
  pubmed Hu Z, Wang X, Chen C, Wang Y 2026 Jul 17 置信度 0.82
• An adaptive client selection method for long tailed scene classification in autonomous driving.
  Collaborative autonomous driving utilizing Federated Learning (FL) is frequently constrained by long-tailed data distributions and perceptual imbalances. Implementing federated learning for environmental scene classification in autonomous driving faces severe …
  pubmed Wen S, Wang X 2026 Jul 17 置信度 0.82
• Resilient federated intrusion detection with explainable AI: a robust CNN-LSTM architecture for extreme non-IID data distributions.
  The rapid proliferation of Internet of Things (IoT) devices has led to a significant rise in security issues, as traditional centralized intrusion detection systems face difficulties in handling issues such as privacy concerns, communication bottlenecks, and h…
  pubmed Moussaoui JE, Kmiti M, Maleh Y, Gholami KE 2026 Jul 15 置信度 0.82
• Ethical and Governance Challenges of AI in Medical Imaging and Diagnostics: A Systematic Survey and Policy Framework Recommendations.
  Background/Objectives: Artificial intelligence (AI) is increasingly embedded within diagnostic imaging workflows, reshaping clinical decision-making, health system governance, and regulatory oversight. While technical advances in radiological AI have accelerat…
  pubmed Athukorala D, Ahmed K, Nowrozy R 2026 Jul 2 置信度 0.82
• Cross-domain edge AI framework for unified threat intelligence in smart grid-EV- VANET ecosystems using lightweight federated learning.
  The convergence of smart grids, electric vehicles (EVs), and Vehicular Ad Hoc Network (VANET) infrastructures has created a rapidly evolving cyber-physical ecosystem that necessitates real-time, privacy-preserving, and intelligent threat detection at the edge.…
  pubmed Swaminathan S, Avudaiappan T, Baazeer Ahamed B, Joseph ER 2026 Jul 14 置信度 0.82
• Building the foundations for global data banking in digital phenotyping for mental health.
  Mental illness is a leading cause of global disability, underscoring the urgent need for scalable, data-driven approaches to early identification and intervention. Passive sensing technologies in mobile and wearable devices enable continuous and unobtrusive me…
  pubmed O'Dea B, Naz S, McLoughlin LT, Whitton AE 2026 Jul 13 置信度 0.82
• FuGuard: Client-Level Federated Unlearning via Generative Surrogates and Optimal Transport.
  Federated learning (FL) is a widely adopted paradigm that enables collaborative model training while preserving data privacy. As concerns around data poisoning and the "right to be forgotten" continue to grow, federated unlearning, which is the ability to remo…
  pubmed Qi P, Annunziata D, Jappelli C, Giampaolo F 等 2026 Jul 13 置信度 0.82
• Vibrational Spectroscopy of Clinical Biofluids: Advances in FTIR and Raman-Based Biomarker Discovery for Disease Diagnosis and Monitoring.
  Human biofluids carry a continuously updated molecular record of systemic health, yet their diagnostic potential remains largely untapped by conventional single-analyte assay platforms. Fourier-transform infrared and Raman spectroscopy, including attenuated to…
  pubmed Polu PR 2026 Jul 13 置信度 0.82
• Imaging studies for predicting hematoma expansion: from traditional imaging signs to artificial intelligence-based multimodal fusion.
  Hematoma expansion (HE) is a critical and modifiable event following acute intracerebral hemorrhage (ICH). Predicting HE accurately can inform individualized treatment and improve patient outcomes. This review systematically outlines the evolution of imaging-b…
  pubmed Wu J, Sheng J, Xiao Y, Wu F 等 2026 置信度 0.82
• GeoGuard-PTI: a geo-temporal predictive threat intelligence framework with spatiotemporal attack forecasting and closed-loop adaptive defense.
  Due to being reactive in nature, most network security frameworks focus on identifying attacks as they take place or reconstructing intrusion sequences once they have already occurred. This paper presents GeoGuard-PTI, an innovative Geo-Temporal Predictive Thr…
  pubmed Manivannan A, Amalanathan A 2026 置信度 0.82
• Generalization over accuracy: A cross-dataset, explainable, and federated learning framework for Parkinson's disease detection.
  Parkinson's disease (PD) is a progressive neurodegenerative disorder for which early screening remains challenging. Although voice-based machine learning approaches have shown promise as non-invasive screening tools, most existing studies rely on single-datase…
  pubmed Ahammad I 2026 Jan-Dec 置信度 0.82
• Federated Computing in Orthopaedic Surgery: A Paradigm Shift in Collaborative Multicenter Research.
  ➢ Multicenter studies remain rare in orthopaedics (9.9% of recent publications) due to regulatory complexity, restrictive data-sharing policies, and administrative delays, despite their proven value in generating robust, generalizable evidence. ➢…
  pubmed Hill BG, Nyul TE, Moschetti WE, Schilling PL 2026 Aug 19 置信度 0.82
• ReFIT: Federated Transfer Learning for Sequential Prediction and Uncertainty Quantification Using Streaming EHR Data.
  Modern biomedical data are increasingly collected across multiple institutions and time periods, creating opportunities for improved statistical inference through knowledge transfer, but also posing challenges for privacy, scalability, and distributional heter…
  pubmed Lu Y, Luo L, Gu T 2026 May 23 置信度 0.82
• FET-FIDS: a federated enhanced transformer-based framework for privacy-preserving network intrusion detection.
  The rising rate of interconnected systems, cloud infrastructures, edge environments, and distributed network architectures have greatly exposed the vulnerability of the current digital infrastructures. This has exposed them to more advanced cybercrimes like de…
  pubmed Appadurai JP, Swetha R, Srinivas V, Siripuri K 等 2026 Jul 8 置信度 0.82
• A privacy-preserving rule fusion approach for uncertainty-aware decision-making in posture detection.
  This study introduces a novel approach to constructing rule-based decision systems within a federated learning framework. The proposed rule fusion method is specifically designed for privacy-sensitive applications with uncertainty in data environments. Such ch…
  pubmed Pękala B, Wilbik A, Gil D 2026 Jul 8 置信度 0.82
• Distributed MAC scheduling in IEEE 802.15.7-oriented VLC networks via federated deep reinforcement learning.
  Visible light communication (VLC) networks modeled through a scheduling-level IEEE 802.15.7-oriented PHY/MAC abstraction are sensitive to line-of-sight blockage, receiver orientation, ambient-light noise, heterogeneous traffic loads, and inter-luminaire optica…
  pubmed Salazar IS, Játiva PP, Reyes MC, Ali A 等 2026 Jul 8 置信度 0.82
• Scalable hierarchical federated graph-transformer architecture for efficient multi-modal intrusion detection in 6G UAV-assisted vehicular IoT.
  The increasing growth of 6G-empowered UAV-assisted vehicular IoT systems brings forth unprecedented scalability issues for distributed intrusion detection, especially in the context of non-IID data distributions and heterogeneous edge environments. Centralized…
  pubmed Alnafisah KH, Almutairi AM, Ibraheem A, Almutawa A 等 2026 Jul 8 置信度 0.82
• Reinforcement learning driven edge-cloud coordination for secure and energy efficient IoMT.
  The Internet of Medical Things (IoMT) enables sophisticated medical devices, but it also poses significant challenges in terms of data privacy, real-time processing, and energy efficiency for edge devices with limited resources. In this paper, we propose a hie…
  pubmed Sasikumar SK, Pai TV, Kalidasan K, Gajendran S 2026 置信度 0.82
• Human digital twins in personalized and predictive healthcare: a comprehensive review of technologies, applications, and future directions.
  The role of real-time data, artificial intelligence, and computational modeling is discussed in this review analytics Human Digital Twins (HDTs) creation- virtual persons of personalities patients which advocate predictive simulation to forecast of physiologic…
  pubmed Mohan Babu A, Madhan ES 2026 置信度 0.82
• A blockchain-enabled multi-objective reinforcement learning framework for secure energy- and time-efficient smart path planning in cloud environments.
  Path planning for cloud based autonomous systems such as smart transportation, Internet of Things (IoT) installations and robot fleets need to be secure, energy efficient, time efficient and fulfil privacy constraints. Current reinforcement learning (RL) techn…
  pubmed Dewangan RR, Thombre D, Parganiha V, Verma M 等 2026 Jul 3 置信度 0.82
• An ML-augmented framework for WSN and IoT in 6G networks.
  5G wireless networks have paved the way for intelligent, reliable communication networks with extremely high data rates, ultra-low latency, and highly reliable connectivity. With 6G wireless networks expected to offer up to 1 Tbps data rates with near-zero lat…
  pubmed Khan G, Ali W, Gupta GK, Gola KK 2026 Jul 3 置信度 0.82
• Enabling AI-Based Prediction of Neoadjuvant Treatment Response: A FAIR Multimodal Dataset Within EUCAIM.
  This work presents a FAIR-compliant, multimodal PET-CT and clinical dataset developed within the EUCAIM framework to support future AI-based prediction of response to NST in LABC patients. A real-world dataset was curated, harmonized, and integrated into the E…
  pubmed González López M, Álvarez Pérez RM, Rey Garduño F, Jiménez-Hoyuela García JM 等 2026 Jun 29 置信度 0.82
• Privacy-preserving Virtual Contrast-enhanced MRI for Nasopharyngeal Carcinoma: A Multicenter Study.
  Contrast-enhanced magnetic resonance image (MRI) imaging via administration of contrast agents is critical for diagnosis, staging, and treatment of nasopharyngeal carcinoma (NPC). However, gadolinium-based contrast agents can lead to severe adverse effects, es…
  pubmed Li W, Li Z, Shi Y, Lam S 等 2026 Jul 2 置信度 0.82
• Federated Learning
  crossref Alexander Jung 2026-01-02T02:23:08Z 置信度 0.70
• Title page
  crossref 2025-09-12T12:25:54Z 置信度 0.70
• Machine Learning Foundations for FL
  crossref Alexander Jung 2026-01-02T02:23:17Z 置信度 0.70
• Graph Learning for FL Networks
  crossref Alexander Jung 2026-01-02T03:40:23Z 置信度 0.70
• 2026 2nd International Conference on Federated Learning and Intelligent Computing Systems (FLICS)
  crossref 2026-07-29T19:11:52Z 置信度 0.70
• Federated Dynamic Weighting for Heterogeneous Healthcare Data
  crossref Maryam Moradpour, Anne-Christin Hauschild 2026-07-29T19:11:21Z 置信度 0.70
• Front Matter
  crossref 2026-06-23T12:51:06Z 置信度 0.70
• Impact of Post-Training and Quantization-Aware Training in Federated Learning*
  crossref Farwa Ikram, Dipanwita Thakur, Sadi Alawadi, Antonella Guzzo 等 2026-07-29T19:11:57Z 置信度 0.70
• Federated SHAP: Privacy-Preserving and Consistent Post-hoc Explainability in Federated Learning
  crossref Pietro Ducange, Francesco Marcelloni, Giustino Claudio Miglionico, Alessandro Renda 等 2026-01-20T20:49:58Z 置信度 0.70
• SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies
  crossref Mohamed Nabih Ali, Daniele Falavigna, Alessio Brutti 2026-07-29T19:10:04Z 置信度 0.70
• Privacy-Preserving Federated Learning for Healthcare IoT Systems
  <p><span>The rapid adoption of Internet of Things (IoT) devices in healthcare has enabled continuous patient monitoring through wearable sensors, ECG devices, and smart medical equipment. While these technologies generate valuable real-time data fo…
  crossref Preethi N 2026-01-26T15:57:17Z 置信度 0.70
• pFedUL: Layer-Aware Federated Unlearning for Personalized Federated Learning
  crossref Zhuodong Liu, Xiangyu Li, Zhihao Zhang 2026-07-08T08:59:48Z 置信度 0.70
• FedSALAT: Adaptive Buffer-Based Active Learning for Federated Data Streams
  crossref Prajit T Rajendran, Fabio Arnez, Huascar Espinoza, Agnes Delaborde 等 2026-07-29T19:12:51Z 置信度 0.70
• Generative AI with federated learning
  crossref Zhuoyu Yao, Dong Yang, Yue Wang 2026-06-26T13:39:59Z 置信度 0.70
• FLICS 2026 Committees
  crossref 2026-07-29T19:11:59Z 置信度 0.70
• FL Algorithms
  crossref Alexander Jung 2026-01-02T02:23:52Z 置信度 0.70
• Index
  crossref 2026-06-23T12:51:06Z 置信度 0.70
• Trustworthy FL
  crossref Alexander Jung 2026-01-02T02:26:44Z 置信度 0.70
• SLVR: Securely Leveraging Client Validation for Robust Federated Learning
  crossref Jihye Choi, Sai Rahul Rachuri, Ke Wang, Somesh Jha 等 2026-05-22T12:25:02Z 置信度 0.70
• FLICS 2026 Copyright
  crossref 2026-07-29T19:12:25Z 置信度 0.70
• Battery State of Health Estimation via Federated Learning on Diverse Data from Multiple Sources
  crossref Vesna Dimitrievska, Andrea Urgolo, Manuel Freiberger, Katrin Unger 2026-07-29T19:12:35Z 置信度 0.70
• GuidaPA: Privacy-Preserving Chatbot for Public Administration via Federated Learning
  crossref Daniel M. Jimenez-Gutierrez, Albenzio Cirillo, Raffaele Nicolussi, Alessio Beltrame 等 2026-07-29T19:10:36Z 置信度 0.70
• Also of Interest
  crossref 2026-06-23T12:51:06Z 置信度 0.70
• FedRecall: Gradient History Replay for Cold-Start Clients in Federated Learning
  crossref Addi Ait-Mlouk, Omar Ait-Mlouk, Fatiha Ait Baali, Chaima Lhasnaoui 2026-07-29T19:10:09Z 置信度 0.70
• Physics-Informed Decentralized Federated Learning (PIDFL): Integrating Domain Knowledge into Federated Systems
  crossref Rakesh Reddy Thalakanti 2026-07-08T11:21:13Z 置信度 0.70
• Leveraging Federated Learning for Predicting Kidney Graft Survival Using OPTN Dataset
  crossref Aman Wakade, Aaisha Makkar, Benjamin Hutchings, Myra Conway 2026-07-29T19:11:02Z 置信度 0.70
• Proceedings of the International Workshop on Secure and Efficient Federated Learning
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