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• Communication-Efficient Federated Learning in Wireless-Edge Architecture
  crossref Sugandh Gupta, Sapna Katiyar 2022-02-02T12:03:00Z 置信度 0.70
• Content-Aware Client Selection for Communication-Efficient Federated Learning
  crossref Zhefeng Qiao 2025-07-22T03:30:09Z 置信度 0.70
• Understanding, Improving, and Implementing Federated Learning on Heterogeneous Data
  crossref Tailin Zhou 2025-09-18T23:04:14Z 置信度 0.70
• Sirilla
  crossref Andrew Selvia 2025-08-26T21:05:06Z 置信度 0.70
• Federated Learning Using Tensor Flow
  crossref Tanu Solanki, Bipin Kumar Rai, Shivani Sharma 2022-02-02T12:03:00Z 置信度 0.70
• Addressing stale gradients in asynchronous federated deep reinforcement learning
  crossref Justin Stanley 2024-03-29T20:32:58Z 置信度 0.70
• A Federated Learning Approach for ResourceConstrained IoT Security Monitoring
  crossref P Sakthibalan, M Saravanan, V Ansal, Amuthakkannan Rajakannu 等 2023-11-16T06:04:28Z 置信度 0.70
• FreezeFL: Accelerating Federated Learning in Heterogeneous Edge Devices by Layer Freezing
  crossref Yu-Min Chou, Fu-Chiang Chang, Jerry Chou 2026-07-29T19:15:18Z 置信度 0.70
• Stacking Ensemble and Federated Learning for IoT Intrusion Detection
  The number of Internet of Things (IoT) devices has increased considerably in the past few years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As part of a defense in depth approach to network security, intrusion detection sys…
  crossref Riccardo Lazzarini 2023-12-19T14:26:35Z 置信度 0.70
• Contents
  crossref 2025-09-12T12:25:54Z 置信度 0.70
• Index
  crossref 2025-09-12T12:25:54Z 置信度 0.70
• Bayesian model compression and federated learning via variational inference
  crossref Chengyu Xia 2024-12-29T23:00:52Z 置信度 0.70
• Privacy-aware continuous federated biometric authentication (PACFBA) using federated deep learning: a novel usable security framework.
  With the rapid growth of mobile, IoT, and edge-based ecosystems, the need for secure, seamless, and privacy-preserving authentication mechanisms has become increasingly critical. Traditional authentication methods, such as passwords and single-step biometrics,…
  pubmed Al Abdulwahid A, Abdulwahid Al Abdulwahid 2026 置信度 0.82
• The Deep Learning Evolution in Wireless Physical Layer Communications: Applications, Challenges, and Evolutionary Directions.
  With the continuous evolution toward sixth-generation (6G) wireless communication systems, emerging scenarios such as terahertz transmission, integrated sensing and communication (ISAC), and ultra-massive multiple-input multiple-output (MIMO) have significantl…
  pubmed Xu H, Liang Y, Xie R, Kong Y 2026 Jun 5 置信度 0.82
• A Comprehensive and Unified Survey on Blockchain-Enabled SDN Cybersecurity: Industry Use Cases, Threat Landscapes, Defense Architectures, and Open Challenges.
  The convergence of Software-Defined Networking (SDN) and Blockchain (BC) creates a symbiotic relationship in which SDN's programmable global visibility complements BC's decentralized, immutable trust model to address critical cybersecurity vulnerabilities and …
  pubmed Dudukcu D, Gorgulu AB, Karakus M, Savran Kiziltepe R 等 2026 Jun 5 置信度 0.82
• Federated Privacy-Preserving Multi-Modal Deep Learning for Breast Cancer Diagnosis: A Physics-Aware Approach.
  Background/Objectives: Breast cancer remains a leading cause of cancer-related mortality among women worldwide. This study presents a systematically justified multi-modal breast cancer classification pipeline that combines established, physically motivated pre…
  pubmed Al-Karawi ALS, Mohammedqasim H, Yılmaz R 2026 置信度 0.82
• Computational pathology model to predict recurrence-free survival in NMPUC patients on BCG-therapy.
  Urothelial carcinoma, predominantly appearing as non-muscle-invasive papillary urothelial carcinoma (NMIPUC), exhibits wide clinical variability. Accurate pathological staging and grading are essential for effective risk stratification and treatment decisions.…
  pubmed Lin YC, Drachneris J, Rasmusson A, Fabijonavicius M 等 2026 Jun 11 置信度 0.82
• High-throughput analysis of multimodal monitoring data: the role of machine learning in early warning systems for high-risk neonates.
  The neonatal intensive care unit (NICU) generates vast amounts of high-throughput, multimodal monitoring data, offering unprecedented potential for identifying early signs of clinical deterioration in high-risk neonates. However, the traditional threshold-base…
  pubmed Huo H, Lu Y, Zhou J, Zhang L 等 2026 Jun 11 置信度 0.82
• From Stochastic Conjugate Gradient to Stochastic Second-Order Optimization, Driven by Conjugate Coefficient With Second-Order Information.
  Conjugate gradient (CG) and second-order information (SOI) receive increasing interest due to their crucial role in improving stochastic first-order (SFO) algorithms for solving machine learning problems. Although a variety of stochastic CG (SCG) and stochasti…
  pubmed Yang Z 2026 Jun 11 置信度 0.82
• Federated deep reinforcement learning for privacy-preserving offloading in vehicular edge computing.
  With the rapid development of Internet of Vehicles (IoV) applications, the demand for serving computation-intensive and delay-sensitive tasks, which are executed in a dynamic mobility environment, continues to grow, while the embedded computing power carried b…
  pubmed Momani AM, Alsekait DM, Al-Khasawneh MA, Othman SH 等 2026 置信度 0.82
• An adversarial-resilient intrusion detection framework for internet of medical things (IoMT) using digital twin-enabled behavioral threat modeling and federated hybrid ensemble learning.
  The Internet of Medical Things (IoMT) has transformed healthcare by enabling continuous patient monitoring and remote diagnostics. However, this growth introduces considerable security challenges. This paper examines vulnerabilities in IoMT devices to advanced…
  pubmed Alkhattabi K, Belhaj S, Selecky J, Talha M 2026 置信度 0.82
• The Intelligence Revolution in Biosensing: Transforming Raw Data into Smart Clinical Diagnostics.
  Artificial intelligence (AI) is revolutionizing nanobiotechnology-enabled biosensing by combining advanced nanomaterials with intelligent data analytics to create next-generation diagnostic platforms. This review summarizes recent progress in AI-integrated nan…
  pubmed Ramadan O, A Rudayni H, El-Raheem HA, Helim R 等 2026 Jun 10 置信度 0.82
• Federated generative prompt learning with vision foundation models: universal efficient multi-center medical image analysis.
  Federated medical AI revolutionizes multi-center collaboration, while communication cost, data scarcity, and heterogeneity still limit its practical deployment. Foundation models (FMs) offer a promising avenue for addressing these challenges, owing to their ge…
  pubmed Lin X, Chen Y, Wu J, Xu C 等 2026 Jun 10 置信度 0.82
• Federated orthogonal learning for detection of liver lesions from multi-phase contrast-enhanced CT images.
  Multi-phase contrast-enhanced CT (CECT) scans are often scattered across multiple institutions and contain incomplete phase in parts of institutions due to the strict data-protection regulations and the disparity of phase integrality. While federated learning …
  pubmed Wu L, Lin H, Hu F, Shen K 等 2026 Jun 8 置信度 0.82
• Graph neural networks for networked analysis of gestational diabetes risk factors: a multi method framework.
  Gestational diabetes mellitus, often known as GDM, is a major health issue that causes complications for mothers and requires patient data prediction models that are complex and variable. The research in question makes use of graph-based learning in order to i…
  pubmed Lella KK, Nabi SA, Sirisha U, Nagamani GM 等 2026 Jun 9 置信度 0.82
• Federated Clustering: An Overview of Algorithm Evolution and Research Prospects.
  As a new paradigm that integrates clustering with federated learning, federated clustering (FC) has recently attracted increasing attention, as it addresses the practical issue of privacy protection in distributed data. In this paper, we provide a comprehensiv…
  pubmed Ding S, Li C, Guo L, Yang Q 2026 置信度 0.82
• Artificial intelligence in clinical physiology: System-wise applications in diagnostics, monitoring, and medical education.
  Artificial Intelligence (AI) is gradually revolutionizing clinical physiology by enhancing diagnostic capabilities, fostering real-time monitoring, and enabling personalized medical education. Its incorporation into various physiological domains and wearable h…
  pubmed Chhabra C, Saroha R, Kosvi M, Singh S 等 2026 Mar 置信度 0.82
• Radiomics: Current Applications and Future Directions.
  Radiomics enables high-throughput extraction of quantitative imaging features to decode tumor phenotypes and biological behaviors, representing a transformative noninvasive tool for precision oncology. In recent years, radiomics has rapidly evolved from static…
  pubmed Shao J, Wei M, Li K, Lv G 等 2026 Jun 置信度 0.82
• Privacy-aware distributed intelligence with tokenized trust for low-latency task offloading in 6G vehicular edge networks.
  The ultra-dense vehicle scenarios envisioned in 6G put high requirements on ultra-low latency, secure cooperation, and efficient task offloading decisions. Existing systems usually optimize latency or energy independently but ignore joint privacy problems and …
  pubmed Alsaffar M, Abouelkheir E, Alawad WM, Alsayfi MS 等 2026 Jun 6 置信度 0.82
• Hybrid CNN BiLSTM architecture for smart grid cyberattack detection using smart meter data.
  Real-time cyber-attack intrusion detection faces serious challenges in the smart grid communications infrastructure, as intrusion tactics become more advanced. Traditional rule-driven detection methods are unable to adapt to diverse attack patterns in modern p…
  pubmed Alamgir FM, Das S, Akand AR, Fariha A 等 2026 Jun 7 置信度 0.82
• Clustering-based federated causal discovery for multicenter clinical data analysis.
  Traditional causal structure learning algorithms struggle in distributed and privacy-sensitive environments, particularly when dealing with non-independent and identically distributed (non-IID) data. To address these limitations, this study proposes the Cluste…
  pubmed Zhang M, Wang H, Zhao J, Wu L 2026 置信度 0.82
• Machine Learning and Deep Learning for Neurological Disease Analysis: A Systematic Review Across Five Major Disorders.
  Artificial Intelligence (AI) has become integral to the research of neurological diseases due to the rapid expansion of neuroimaging, clinical, physiological, and wearable data. However, the concise synthesis of recent machine learning (ML) and deep learning (…
  pubmed Uddin KN, Ghose P, Njie E, Mahmood N 等 2026 置信度 0.82
• Non-IID and aware federated intrusion detection with PBFT with secured model aggregation for multi institutional healthcare internet of things networks.
  Multi-institutional healthcare Internet of Things (IoT) networks face a core challenge between combined intrusion detection and patient data privacy. Raw traffic records cannot be shared across institutional boundaries, yet local models trained on institution-…
  pubmed Sengan S, Shieh CS 2026 置信度 0.82
• Federated autoencoder-based clinical decision framework with hybrid class balancing.
  Despite diagnosis accuracy has been much improved by depending more on deep learning for disease classification, it raises serious concerns about patient data privacy, security, and scalability. Conventional centralized deep learning approaches are vulnerable …
  pubmed Indupalli MR, Pradeepini G 2026 置信度 0.82
• Hybrid optimized focal high-order attention network with descriptor computations for autism spectrum disorder detection in federated learning.
  Autism spectrum disorder is a neurodevelopmental condition that affects the social interaction, and communication ability of persons. Accurate diagnosis can significantly improve quality of life. However, current detection methods often perform sub optimally d…
  pubmed Bhagyalatha U, Sahoo BK, Muppidi S 2026 Oct 置信度 0.82
• Artificial intelligence in prostate cancer imaging: A mini-review of current applications and future directions.
  This mini-review synthesizes evidence from recent studies to provide an updated perspective on current applications, methodological challenges, and future directions for artificial intelligence (AI) in multiparametric magnetic resonance imaging (mpMRI) based p…
  pubmed Ergül MA, Sabur V 2026 Aug 置信度 0.82
• scKSFD: federated distillation model with knowledge sharing for cell type classification of clinical transcriptome data.
  Single-cell RNA sequencing (scRNA-seq) enables high resolution characterization of cellular heterogeneity but poses significant challenges for cross institutional collaboration due to privacy constraints and distributional heterogeneity. To address this proble…
  pubmed Sun N, Guan M, Zhou P, Yau SS 2026 Jun 4 置信度 0.82
• Fully automated system predicts osteoporotic vertebral fracture across institutions using lumbar MRI paraspinal muscle signatures.
  Paraspinal muscle (PM) degeneration is a crucial yet frequently overlooked risk factor for osteoporotic vertebral fractures (OVF). We developed PM Segmentation and Classification of OVF (PMSAC-OVF), a fully automated, multi-institutional system that segments l…
  pubmed Zhang W, Qin Y, Hao Y, Liang W 等 2026 Jun 4 置信度 0.82
• Byzantine robust federated learning for heterogeneous brain MRI using multisignal gradient fingerprinting and adaptive trust aggregation.
  Federated learning enables collaborative training across institutions without centralizing patient data, but remains vulnerable to malicious clients and severe non-IID data heterogeneity. We propose a trust-aware federated learning framework for brain MRI that…
  pubmed Karami M, Kebriaei H, Ghassemi F, Azadegan H 2026 置信度 0.82
• Selective entropy-fused proximal policy optimisation with federated reinforcement learning for intelligent multi-UAV trajectory and communication optimisation.
  The rapid evolution of 5G and emerging 6G networks has increased the demand for wireless communication systems that deliver high capacity, low latency, and adaptability. However, conventional terrestrial infrastructure remains costly and inflexible, particular…
  pubmed Velmurugan M, Velmurugan T 2026 置信度 0.82
• The Internet of Vehicles (IoV) and privacy-preserving systems.
  The Internet of Vehicles (IoV) is changing the contemporary mobility, as it allows real-time communication between vehicles, infrastructure, and cloud services. Nevertheless, such growing connectivity brings on serious privacy, regulatory, and trust issues esp…
  pubmed Zahid N, Tahir S, Algarni F, Tahir H 等 2026 Jun 4 置信度 0.82
• BigOrthoATD.Net: A scalable and adaptable distributed deep learning framework for multi-class orthopedic classification across imaging modalities in low-resourced settings.
  Multi-class medical image classification using DL continues to face major challenges, including managing multi-modal data, adapting to new tasks, handling distributed datasets, and operating under limited computational resources. Existing approaches fail to ad…
  pubmed Alwzwazy HA, Alzubaidi L, Zhao Z, Crawford R 等 2026 Nov 置信度 0.82
• Robust cross-domain generalization using unlabeled target data with source-domain supervision.
  It is often desirable to generalize medical imaging AI models trained with dense annotations to data acquired from different ultrasound scanners or clinical sites; however, retraining these models with new annotations is often difficult and costly. We examine …
  pubmed Zhou Y, Ghosh S, Xie MKY, Kim JJY 等 2026 Aug 15 置信度 0.82
• Artificial intelligence in allergen immunotherapy: toward a proactive and personalized management of allergic diseases.
  The management of immunoglobulin E (IgE)-mediated allergic diseases and allergen immunotherapy (AIT) is complicated by high interindividual variability and the unavailability of reliable predictive biomarkers. Given the complexity of the immune response underl…
  pubmed Gangemi S, Gammeri L 2026 May 26 置信度 0.82
• Artificial intelligence in paediatric chest imaging: applications, challenges, and future directions.
  Paediatric chest imaging is central to diagnosing respiratory and cardiopulmonary disease, particularly in low- and middle-income countries (LMICs) where pneumonia remains a leading cause of childhood mortality and radiology expertise is scarce. Artificial int…
  pubmed Muringathuparambil JJ, Maharaj S, Segal BM, Mahomed N 2026 Jun 3 置信度 0.82
• Towards Straggler-Resilient Split Federated Learning: An Unbalanced Update Approach.
  Split Federated Learning (SFL) enables scalable training on edge devices by combining the parallelism of Federated Learning (FL) with the computational offloading of Split Learning (SL). Despite its great success, SFL suffers significantly from the well-known …
  pubmed Liang D, Zhang J, Chen E, Li Z 等 2025 Dec 置信度 0.82
• Design of an AI-based security anomaly detection system for IoT terminals based on the ViT-transformer fusion model.
  The deep penetration of IoT terminals in water systems, healthcare, transportation, and other fields has exacerbated security threats such as cyber-physical attacks and traffic anomalies. However, traditional anomaly detection methods have limitations such as …
  pubmed Zhang X 2026 Jun 2 置信度 0.82
• A strong robust multi level database image watermark embedding scheme based on the Chinese remainder theorem.
  Due to the fact that most existing digital watermarking schemes can only add watermark information once, repeated additions will overwrite the original watermark information, making it impossible to achieve multi-level traceability of data. In response to the …
  pubmed Geng H, Guo S, Liu Y, Li C 2026 Jun 2 置信度 0.82
• SQUID-COMM: a Colossal Squid-inspired distributed communication framework for real-time multi-node aquaculture monitoring networks with adaptive bioluminescent signaling and neuromorphic edge intelligence.
  Precision aquaculture demands robust communication networks capable of coordinating thousands of distributed sensors across marine and freshwater facilities. Current aquaculture IoT networks face critical challenges including underwater signal attenuation reac…
  pubmed Salem AI, Elbaz M, Khalil HM, Loey M 2026 Jun 2 置信度 0.82
• Artificial intelligence empowered coronary artery imaging: A review.
  Cardiovascular disease is the leading cause of death worldwide, with coronary artery disease the most prevalent cause. Although artificial intelligence has advanced medical imaging, few reviews focus specifically on AI-powered coronary artery imaging. This rev…
  pubmed Wang M, Chen J, Li H, Zhang LB 等 2026 Jun 置信度 0.82
• Heterogeneity-aware personalised federated learning for household energy forecasting on multi-source real-world smart meter data.
  Residential and building-level electricity forecasting is increasingly based on smart-meter streams, but direct data pooling is often difficult because load traces are private, geographically dispersed and statistically different across households and building…
  pubmed Das P, Pandey S, Pandey C, Kumar D 2026 置信度 0.82
• PainFedMVL: A Federated Multi-View Learning Approach for Multi-Level Pain Recognition.
  Pain is a critical clinical indicator in rehabilitation and neurological disorders, yet reliable multi-level recognition remains challenging due to subtle facial variations, inter-subject variability, and heterogeneous clinical data. To address these issues, w…
  pubmed Li D, Yang Z, Xie S 2026 置信度 0.82
• Toward Fair Federated Graph Learning.
  As a privacy-preserving collaborative paradigm, federated graph learning (FGL) enables distributed training of graph neural networks (GNNs) without exposing raw graph data. Subgraph-FL has become the dominant FGL paradigm, yet most studies focus on overall nod…
  pubmed Wu Z, Pang B, Li X, Zhu Y 等 2026 Jun 1 置信度 0.82
• Adversarial Robust Federated Learning for Secure Mortality Risk Prediction using Multi-Institutional Electronic Health Records (EHRs).
  Electronic Health Records (EHRs) are the main source of data that enable data-driven clinical decision-making. However, the sensitive character of EHRs and the strict privacy policies in the healthcare sector make centralized model training difficult or imposs…
  pubmed Chatterjee S, Satpathy S 2026 May 12 置信度 0.82
• Nanostructured electrode materials and flexible-substrate engineering for wearable multi-analyte biosensors in diabetes monitoring and personalized care: a comprehensive review.
  This review examines the convergence of wearable biosensors and artificial intelligence (AI) in personalized diabetes care. It addresses the limitations of traditional glucose monitoring and underscores the need for continuous, multi-analyte physiological surv…
  pubmed Sodeify R, Seyednazari MA, Dorosti AM, Nourazarian A 2026 Jun 1 置信度 0.82
• Artificial intelligence optimizes immune rejection prediction and management in heart transplantation: a structured narrative review.
  Heart transplantation remains the definitive therapy for end-stage heart failure, yet long-term outcomes are limited by three core clinical bottlenecks in immune rejection management: imprecise preoperative donor-recipient matching, overreliance on invasive en…
  pubmed Chen K, Lai J, Luo Y, Li C 等 2026 置信度 0.82
• Artificial intelligence for antimicrobial resistance: advancing reproducibility, interpretability, and clinical deployment.
  The shift of artificial intelligence for antimicrobial resistance (AI-AMR) from proof-of-concept studies to clinically embedded decision support critically hinges on establishing rigorous reproducibility, interpretability, and evaluation standards aligned with…
  pubmed Sardar S, Dash S, Roychowdhury P, Solanki J 等 2026 May 4 置信度 0.82
• Multiscale predictive cellular modeling: integrating hypothesis grammars, digital twins, and multi-omics for In silico oncology and precision theranostics.
  Predictive multiscale cellular modeling is emerging as a consequential direction in precision medicine, converging hypothesis grammars, digital twins, and integrative genomics to interrogate tumor-immune dynamics, therapeutic resistance, and cellular plasticit…
  pubmed Gopukumar ST, Dwivedi D, Rahamathulla M, Ahmed MM 等 2026 May 29 置信度 0.82
• Enabling the analysis of patient-level data across jurisdictions for research use: a real-world exploration of a federated likelihood approach.
  The disclosure of health data is governed by strict privacy regulations which significantly restrict the transfer of data across jurisdictions. These limitations restrict the scope of health research, particularly the ability to conduct studies that span multi…
  pubmed Harmon M, Li N, Sajobi T, Holodinsky J 等 2026 置信度 0.82
• Artificial intelligence and transforming cancer care.
  Artificial Intelligence (AI) is reshaping oncology by addressing key limitations in traditional cancer care and enabling data-driven, personalized approaches from diagnosis to treatment. This review explores the transformative role of AI across the cancer care…
  pubmed Reddy AM, Kaur G, Ribaya VSD, Ribaya ELA 等 2026 May 28 置信度 0.82
• Artificial intelligence in cancer immunotherapy: current trends in predicting response and personalizing treatment.
  Artificial intelligence (AI) can transform cancer immunotherapy by enabling more accurate prediction of treatment responses, the discovery of specific biomarkers, and the development of personalised treatment plans. Traditional single-marker biomarkers (PD-L1,…
  pubmed Nosa-Ihaza EA, Edeh EC, Geng WB, Okenwa E 2026 May 28 置信度 0.82
• A federated learning-enabled energy-aware anomaly detection algorithm for secure big data analytics in IoT-based smart healthcare systems.
  The rapid expansion of Internet of Things (IoT) devices in smart healthcare systems has led to the generation of large volumes of diverse medical data. This creates challenges in ensuring secure, scalable, and energy-efficient anomaly detection. Traditional ce…
  pubmed Al-Alshaikh HA 2026 置信度 0.82
• A federated deep learning framework with distributed hybrid character-level and attention mechanisms for scalable and cost-efficient fake news detection.
  Fake news detection is an essential task for media and news organizations to maintain the trust and reliability of the published content. Due to the rapid growth of online users and the spread of misinformation through malicious sources, the fake news circulat…
  pubmed Nithya K, Dhivyaa CR 2026 May 27 置信度 0.82
• Decentralized EM algorithm for Gaussian mixtures under data heterogeneity and partial labeling.
  We systematically study several network-based Expectation-Maximization (EM) algorithms for the Gaussian mixture model within decentralized federated learning (DFL). Our theoretical investigation reveals that directly extending the classic EM algorithm to DFL l…
  pubmed Li X, Wu S, Du B, Wang H 2026 Apr 9 置信度 0.82
• Personalized Federated Actor-Critic Learning for Joint Cost-Comfort Optimization in Energy Communities.
  Home energy management systems (HEMS) aim to provide intelligent control of the thermal comfort inside smart buildings with the minimum energy cost, while satisfying the energy consumption requests and increasing the use of energy from renewable sources. The c…
  pubmed Spantideas S, Giannopoulos A 2026 May 8 置信度 0.82
• AI and Machine Learning for Proteomics-Driven Drug Discovery: Methods, Tools, and Best Practices.
  Proteomics has become central to pharmacological research by providing quantitative readouts of protein abundance, post-translational modifications, interactions, and spatial context. However, proteomic datasets are high-dimensional, heterogeneous, and frequen…
  pubmed Basak S 2026 May 20 置信度 0.82
• Artificial Intelligence for Spatial Immunometabolic Analysis of the Tumor Microenvironment: Current Evidence and Future Directions.
  The tumor microenvironment [TME] is a dynamic ecosystem where spatial organization and metabolic reprogramming play a crucial role in immune response, tumor progression, and therapeutic response. Recent breakthroughs in spatial transcriptomics, metabolomics, a…
  pubmed Abdullah I, Khan SS, Khan S, Abou D 等 2026 May 3 置信度 0.82
• Artificial Intelligence in Oncology: A Comprehensive Cross-Cancer Translational Readiness Analysis Across 18 Malignancies.
  Artificial intelligence (AI) is reshaping oncology at every stage of the cancer care pathway, from population-level screening through molecular diagnosis, treatment planning, and post-treatment surveillance. Despite an exponential growth in AI oncology publica…
  pubmed Kuchana SK, Repalle UK, Alahari NV, Kondamuri M 等 2026 May 10 置信度 0.82
• An intelligent cloud firewall framework for multi-cloud security using lstm anomaly detection and federated learning.
  The evolving nature of the threat landscape against cloud services is outpacing the capabilities of traditional security measures. Current firewall implementations in cloud services may provide a foundational layer of security, but they have significant limita…
  pubmed V A, S KSR 2026 May 27 置信度 0.82
• Sustainable smart sensing and AI-driven platforms for real-time detection and monitoring of mycotoxins across the food supply chain.
  This review aims to critically evaluate sustainable smart sensing technologies and AI-driven platforms for real-time mycotoxin detection, highlighting innovations, integration across the food supply chain, current limitations, and future directions for safer, …
  pubmed Adeyeye BR, Adeyeye SAO 2026 May 26 置信度 0.82
• A novel intrusion detection system for IIoT in 5G networks using attention-augmented federated learning and lightweight transformer architectures.
  The swift proliferation of Industrial Internet of Things (IIoT) devices within 5G networks has intensified cybersecurity vulnerabilities owing to their limited processing capabilities and fluctuating network conditions. This work presents an innovative intrusi…
  pubmed Du J 2026 May 26 置信度 0.82
• Self-defending 6G networks through AI-driven adaptive decoy generation at the edge.
  The advent of 6G networks is that , they promise to deliver high connectivity as well as a much larger attack surface, traditional security models are found to be wanting. In this paper, we propose an Adaptive Decoy Generation Framework that is able to deliver…
  pubmed M J RM, G PR, Gopal P, Sathyamoorthy M 等 2026 May 26 置信度 0.82
• Federated Multi-View Unsupervised Feature Selection via Bio-Inspired Hierarchical-Cognitive Tianji's Horse Racing Optimization and Tensor Learning.
  As multi-view datasets expand across diverse practical fields, feature selection (FS) has become an indispensable preparatory stage for machine learning models. Nevertheless, real-world multi-view data is often unlabeled and distributed among isolated clients,…
  pubmed Cheng R, Sun Z, Qi K, Wu W 等 2026 置信度 0.82
• Construction of a sports bio mechanical injury prediction and AI warning system based on wearable sensors.
  Real-time warning and prevention of sports injuries are core challenges in the fields of sports medicine and health management. Traditional methods rely on single sensor data and static threshold rules, which have problems such as single monitoring dimension, …
  pubmed Feng Y, Ma Z 2026 May 26 置信度 0.82
• AI and longevity medicine: Unlocking predictive and preventive strategies for healthy aging.
  Longevity medicine is transforming healthcare by shifting the focus from disease treatment toward the preservation of function, resilience, and healthspan. In parallel, artificial intelligence (AI) has emerged as a powerful catalyst accelerating this transitio…
  pubmed Green JB, Haykal D 2026 May 25 置信度 0.82
• A federated blockchain framework for secure and intelligent smart farming in sustainable industrial agriculture.
  The fast growth of smart farming technologies and Internet of Things (IoT) sensors has transformed the agricultural sector, but has brought some fundamental problems, such as data privacy, scalability, and trust in distributed systems. In this paper, AgriChain…
  pubmed Jaffar AY 2026 置信度 0.82
• Application of Artificial Intelligence Frameworks in Development of Medical Imaging Diagnosis Systems: A Comprehensive Review of Novel Methodologies, Clinical Validation, Performance Optimization, and Future Perspectives
  Artificial intelligence (AI) has revolutionized medical imaging with automated disease detection, image segmentation, diagnosis, prognosis prediction, and clinical decision support across various imaging modalities, such as X-ray, computed tomography (CT), mag…
  datacite Susreeti Sur, Rakesh Kumar, Mandal, Debanil, Chanda 2026 置信度 0.66
• EELNet–ALOCO: Source Code and Three-Month IoT Dataset for Energy-Efficient Smart Building Management
  This repository contains the source code and representative dataset for the EELNet–ALOCO smart-building energy control framework. The framework combines the Edge-Efficient Learning Network with Adaptive Localized Cooperative Optimization for decentralized edge…
  datacite Merrisha, John, P, ARULMATHI 2026 置信度 0.66
• EELNet–ALOCO: Source Code and Three-Month IoT Dataset for Energy-Efficient Smart Building Management
  This repository contains the source code and representative dataset for the EELNet–ALOCO smart-building energy control framework. The framework combines the Edge-Efficient Learning Network with Adaptive Localized Cooperative Optimization for decentralized edge…
  datacite Merrisha, John, P, ARULMATHI 2026 置信度 0.66
• A Comparative Analysis of Artificial Intelligence and Business Intelligence using Big Data Analytics
  This research presents a comparative analysis of Artificial Intelligence (AI) and Business Intelligence (BI) using Big Data Analytics. The study evaluates multiple machine learning algorithms, including Random Forest, Neural Networks, Support Vector Machines, …
  datacite vegineni, Gopi Chand, ADDANKI, SIREESHA, Mandal, Rishabh, K, Arun Kumar 等 2024 置信度 0.66 Artificial IntelligenceBusiness IntelligenceBig Data AnalyticsMachine LearningRandom Forest
• A Comparative Analysis of Artificial Intelligence and Business Intelligence using Big Data Analytics
  This research presents a comparative analysis of Artificial Intelligence (AI) and Business Intelligence (BI) using Big Data Analytics. The study evaluates multiple machine learning algorithms, including Random Forest, Neural Networks, Support Vector Machines, …
  datacite vegineni, Gopi Chand, ADDANKI, SIREESHA, Mandal, Rishabh, K, Arun Kumar 等 2024 置信度 0.66 Artificial IntelligenceBusiness IntelligenceBig Data AnalyticsMachine LearningRandom Forest
• A Quantum-Resilient Federated Learning Framework for Secure Smart Grid
  Wide-area monitoring systems built on phasor measurement units (PMUs) underpin real-time stability assessment in transmission grids, yet their measurement and communication paths present an attack surface that conventional intrusion detection addresses only pa…
  datacite Tank, Divyam, Singh, Dr. Sushil Kumar 2026 置信度 0.66 Post Quantum EncryptionSmart GridBlockchainSynchrophasorCryptography
• A Quantum-Resilient Federated Learning Framework for Secure Smart Grid
  Wide-area monitoring systems built on phasor measurement units (PMUs) underpin real-time stability assessment in transmission grids, yet their measurement and communication paths present an attack surface that conventional intrusion detection addresses only pa…
  datacite Tank, Divyam, Singh, Dr. Sushil Kumar 2026 置信度 0.66 Post Quantum EncryptionSmart GridBlockchainSynchrophasorCryptography
• ML-Based Predictive Autoscaling on Aws
  Traditional cloud auto-scaling systems rely on static threshold-based rules that react only after workload changes occur, leading to delayed responses, inefficient resource utilization, and increased latency. To address these limitations, this paper proposes a…
  datacite Mr. B. Sundaresan, Ajith Kumar A, Jaikiran J, Mano M, Yaswanth Sai R 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
• ML-Based Predictive Autoscaling on Aws
  Traditional cloud auto-scaling systems rely on static threshold-based rules that react only after workload changes occur, leading to delayed responses, inefficient resource utilization, and increased latency. To address these limitations, this paper proposes a…
  datacite Mr. B. Sundaresan, Ajith Kumar A, Jaikiran J, Mano M, Yaswanth Sai R 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
• Explainable Credit Card Fraud Detection Using LightGBM And SHAP-Guided Feature Selection: A Review
  Digital payment ecosystems have expanded both the volume and complexity of transaction data, widening the opportunity for fraud while raising customer, operational, and regulatory expectations that automated decisions remain explainable. This review consolidat…
  datacite Vijay Saini, Jitender Kumar 2026 置信度 0.66
• Explainable Credit Card Fraud Detection Using LightGBM And SHAP-Guided Feature Selection: A Review
  Digital payment ecosystems have expanded both the volume and complexity of transaction data, widening the opportunity for fraud while raising customer, operational, and regulatory expectations that automated decisions remain explainable. This review consolidat…
  datacite Vijay Saini, Jitender Kumar 2026 置信度 0.66
• A Quantum-Edge Deep Reinforcement Learning Framework For Adaptive And Privacy-Preserving Dynamic Pricing In E-commerce
  The rapid rise of e-commerce platforms has created a need for complex pricing systems that react to market conditions in real-time to improve market share and customer satisfaction. In this paper, we present a new Edge-AI powered situational pricing optimizati…
  datacite Mr. Akula Sri Naga Sai Veera Pawan Anirudh, Mrs. G Prameela 2026 置信度 0.66
• A Quantum-Edge Deep Reinforcement Learning Framework For Adaptive And Privacy-Preserving Dynamic Pricing In E-commerce
  The rapid rise of e-commerce platforms has created a need for complex pricing systems that react to market conditions in real-time to improve market share and customer satisfaction. In this paper, we present a new Edge-AI powered situational pricing optimizati…
  datacite Mr. Akula Sri Naga Sai Veera Pawan Anirudh, Mrs. G Prameela 2026 置信度 0.66
• DIFFERENTIALLY PRIVATE FEDERATED LEARNING WITH BYZANTINE-ROBUST AGGREGATION: A CROSS-DOMAIN FRAMEWORK FOR SECURE MODEL TRAINING IN BANKING AND HEALTHCARE SYSTEMS
  datacite Srikumar Nayak 2024 置信度 0.66
• DIFFERENTIALLY PRIVATE FEDERATED LEARNING WITH BYZANTINE-ROBUST AGGREGATION: A CROSS-DOMAIN FRAMEWORK FOR SECURE MODEL TRAINING IN BANKING AND HEALTHCARE SYSTEMS
  datacite Srikumar Nayak 2024 置信度 0.66
• sofiyastephen1-sudo/Secure-FL-for-UAV: ResFL-UAV v1.0 — Initial Reproducible Release for Manuscript
  ResFL-UAV v1.0 — Initial Reproducible Release for Manuscript This release corresponds to the experimental results reported in the manuscript titled "Resource-Constrained Secure Federated Learning Framework for Unmanned Aerial Vehicles. The release includes: Co…
  datacite sofiyastephen1-sudo 2026 置信度 0.66
• sofiyastephen1-sudo/Secure-FL-for-UAV: ResFL-UAV v1.0 — Initial Reproducible Release for Manuscript
  ResFL-UAV v1.0 — Initial Reproducible Release for Manuscript This release corresponds to the experimental results reported in the manuscript titled "Resource-Constrained Secure Federated Learning Framework for Unmanned Aerial Vehicles. The release includes: Co…
  datacite sofiyastephen1-sudo 2026 置信度 0.66
• randdwriting2026/FR-26-01: CryptographicFogServer
  Cryptographic Fog-Server and Deep Federated Learning Architecture
  datacite randdwriting2026 2026 置信度 0.66
• randdwriting2026/FR-26-01: CryptographicFogServer
  Cryptographic Fog-Server and Deep Federated Learning Architecture
  datacite randdwriting2026 2026 置信度 0.66
• Data and Code for MedSparseFL
  Official source code for the proposed support-aware sparse federated learning framework. This implementation includes gradient score estimation, sparse communication, and robust aggregation mechanisms designed for heterogeneous (non-IID) environments.
  datacite Zhu, Bian, Niu, Ling 2026 置信度 0.66
• Data and Code for MedSparseFL
  Official source code for the proposed support-aware sparse federated learning framework. This implementation includes gradient score estimation, sparse communication, and robust aggregation mechanisms designed for heterogeneous (non-IID) environments.
  datacite Zhu, Bian, Niu, Ling 2026 置信度 0.66
• Global Legal Architecture for Foundation Model-Driven Multimodal Signal Processing: Integrating Federated Self-Supervised Learning, Cross-Border Data Sovereignty, and Algorithmic Liability into Transnational Regulatory Compliance Frameworks Prepared and Authored by Dr. Mohamed Kamal Arafa El-Rakhawi International Law & Emerging Technologies Governance
  Global Legal Architecture for Foundation Model-Driven Multimodal Signal Processing: Integrating Federated Self-Supervised Learning, Cross-Border Data Sovereignty, and Algorithmic Liability into Transnational Regulatory Compliance Frameworks Prepared and Author…
  datacite elrakhawi, mohamed kamal arafa 2026 置信度 0.66
• Global Legal Architecture for Foundation Model-Driven Multimodal Signal Processing: Integrating Federated Self-Supervised Learning, Cross-Border Data Sovereignty, and Algorithmic Liability into Transnational Regulatory Compliance Frameworks Prepared and Authored by Dr. Mohamed Kamal Arafa El-Rakhawi International Law & Emerging Technologies Governance
  Global Legal Architecture for Foundation Model-Driven Multimodal Signal Processing: Integrating Federated Self-Supervised Learning, Cross-Border Data Sovereignty, and Algorithmic Liability into Transnational Regulatory Compliance Frameworks Prepared and Author…
  datacite elrakhawi, mohamed kamal arafa 2026 置信度 0.66
• DEx-FCL: Reproducibility package for adaptive Edge-IoT security management
  Reproducibility package update for the manuscript "DEx-FCL: Drift- and Explanation-Consistent Federated Continual Learning for Adaptive Edge-IoT Security Management." Version 1.0.1 adds the complete real-benchmark result CSVs and generated manuscript figures u…
  datacite P, Arul Selvam 2026 置信度 0.66