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• Differential Privacy Techniques in Machine Learning for Health Record Analysis
  europepmc 2025 置信度 0.80
• Data Compliance Utilization Method Based on Adaptive Differential Privacy and Federated Learning.
  europepmc 2026 置信度 0.80
• Sensitivity-Aware Differential Privacy for Federated Medical Imaging.
  europepmc 2025 置信度 0.80
• Privacy-Preserving Federated Learning Approach Based on Hensel’s Compression and Differential Privacy
  europepmc 2025 置信度 0.80
• A Bilayer Feature Fusion Framework for Pan-Cancer Survival Prediction Based on Multihead Attention and Adaptive Differential Privacy: Model Development and Validation Study.
  europepmc 2026 置信度 0.80
• Illuminating the Landscape of Differential Privacy: An Interview Study on the Use of Visualization in Real-World Deployments.
  europepmc 2025 置信度 0.80
• An Asynchronous Federated Learning Aggregation Method Based on Adaptive Differential Privacy
  europepmc 2025 置信度 0.80
• Federated Continual Learning with Adaptive Differential Privacy and Client-Side Drift Detection for Evolving Medical Imaging Datasets
  Abstract This paper presents a novel Federated Continual Learning framework for medical imaging that enables continuous model updates across multiple hospitals without central data sharing. Our approach addresses critical challenges in healthcare AI: data priv…
  europepmc Nnaemeka Kingsley Ugwumba 2025 置信度 0.80
• Attack concealment for cyber-physical systems using a mechanism borrowing from differential privacy.
  europepmc 2025 置信度 0.80
• Enhancing privacy protection of physical examination data through synthetic algorithms based on differential privacy.
  europepmc 2025 置信度 0.80
• Equitable differential privacy.
  Differential privacy (DP) has been in the public spotlight since the announcement of its use in the 2020 U.S. Census. While DP algorithms have substantially improved the confidentiality protections provided to Census respondents, concerns have been raised abou…
  europepmc Vasundhara Kaul, Tamalika Mukherjee 2024 置信度 0.80
• Differential Privacy Enabled Robust Asynchronous Federated Multitask Learning: A Multigradient Descent Approach.
  europepmc 2025 置信度 0.80
• COVARIANCE LOSS, SZEMEREDI REGULARITY, AND DIFFERENTIAL PRIVACY.
  europepmc 2025 置信度 0.80
• A service-oriented microservice framework for differential privacy-based protection in industrial IoT smart applications.
  europepmc 2025 置信度 0.80
• Analysis, Design, and Implementation of a User-Friendly Differential Privacy Application.
  europepmc 2025 置信度 0.80
• A Combined Approach of Heat Map Confusion and Local Differential Privacy for Anonymization of Mobility Data
  europepmc 2025 置信度 0.80
• FAItH: Federated Analytics and Integrated Differential Privacy with Clustering for Healthcare Monitoring.
  europepmc 2025 置信度 0.80
• Encrypted Spiking Neural Networks Based on Adaptive Differential Privacy Mechanism.
  europepmc 2025 置信度 0.80
• Integrating differential privacy in deep reinforcement learning for sepsis treatment with pulmonary implications.
  europepmc 2025 置信度 0.80
• Federated Analysis With Differential Privacy in Oncology Research: Longitudinal Observational Study Across Hospital Data Warehouses.
  europepmc 2025 置信度 0.80
• Fusion of Personalized Federated Learning (PFL) with Differential Privacy (DP) Learning for Diagnosis of Arrhythmia Disease.
  europepmc 2025 置信度 0.80
• Federated transfer learning with differential privacy for multi-omics survival analysis.
  europepmc 2025 置信度 0.80
• Secure and privacy-preserving surgical instrument segmentation in minimally invasive surgeries using federated differential privacy approach.
  europepmc 2025 置信度 0.80
• Entropy-adaptive differential privacy federated learning for student performance prediction and privacy protection: a case study in Python programming.
  europepmc 2025 置信度 0.80
• Does Differential Privacy Prevent Backdoor Attacks in Practice?
  europepmc 2024 置信度 0.80
• Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification.
  europepmc 2025 置信度 0.80
• Top-<i>k</i> Shuffled Differential Privacy Federated Learning for Heterogeneous Data.
  europepmc 2025 置信度 0.80
• Soft Prompt Tuning via Differential Privacy: Balancing Accuracy and Privacy in Language Models
  Despite its effectiveness, soft prompt tuning approach raises concerns about privacy---we might risk disclosing sensitive information about individuals represented in the data if attackers carefully inspect the learned prompts. To address privacy issues in gen…
  europepmc Junhong Shen 2025 置信度 0.80
• Personalized Federated Learning Scheme for Autonomous Driving Based on Correlated Differential Privacy.
  europepmc 2024 置信度 0.80
• Critical Observability Enforcement in Discrete-event Systems Using Differential Privacy
  In the context of discrete-event systems (DESs), critical states usually refer to a system configuration of interest, describing certain important system properties, e.g., fault diagnosability, state/language opacity, and state/event concealment. Technically, …
  europepmc Jie Zhang, Zhiwu Li 2024 置信度 0.80
• Blockchain Based Secure Federated Learning With Local Differential Privacy and Incentivization.
  europepmc 2024 置信度 0.80
• AWDP-FL: An Adaptive Differential Privacy Federated Learning Framework
  Data security and user privacy concerns are increasingly gaining attention. Federated learning models based on differential privacy offer a distributed machine learning framework that protects data privacy; however, the added noise can impact the model&#03…
  europepmc Zhiyan Chen, Hong Zheng, Gang Liu 2024 置信度 0.80
• Wasserstein Generative Adversarial Networks Based Differential Privacy Metaverse Data Sharing.
  europepmc 2024 置信度 0.80
• Cross-silo Federated Learning with Record-level Personalized Differential Privacy.
  europepmc 2024 置信度 0.80
• Mechanisms for Robust Local Differential Privacy.
  europepmc 2024 置信度 0.80
• A Differential Privacy-Based Approach for Mitigating Data Theft in Ransomware Attacks
  Ransomware attacks have increasingly shifted toward more sophisticated tactics, not only encrypting critical files but also exfiltrating sensitive data, which is then used as leverage in extortion attempts. Addressing this dual threat, a novel framework integr…
  europepmc Merumu Olabim, Amir Greenfield, Arjun Barlow 2024 置信度 0.80
• Navigating the Privacy-Accuracy Tradeoff: Federated Survival Analysis with Binning and Differential Privacy
  Abstract Federated learning (FL) offers a decentralized approach to model training, allowing for data-driven insights while safeguarding patient privacy across institutions. In the Personal Health Train (PHT) paradigm, it is local model gradients from each ins…
  europepmc Varsha Gouthamchand, Johan van Soest, Giovanni Arcuri, Andre Dekker 等 2024 置信度 0.80
• Federated learning and differential privacy: Machine learning and deep learning for biomedical image data classification.
  europepmc 2025 置信度 0.80
• SafeSynthDP: Leveraging Large Language Models for Privacy-Preserving Synthetic Data Generation Using Differential Privacy
  Machine learning (ML) models frequently rely on training data that may include sensitive or personal information, raising substantial privacy concerns. Legislative frameworks such as the General Data Protection Regulation (GDPR) and the California Consumer Pri…
  europepmc Md Mahadi Hasan Nahid, Sadid Bin Hasan 2025 置信度 0.80
• An empirical assessment of differential privacy in real-world observational data: a case-control study of asthma exacerbation in UK Biobank linked with electronic health records.
  europepmc 2025 置信度 0.80
• Federated learning with differential privacy via fast Fourier transform for tighter-efficient combining.
  europepmc 2024 置信度 0.80
• <span style="mso-fareast-font-family: SimSun;">Privacy-Preserving Financial Transaction Pattern Recognition: A Differential Privacy Approach
  europepmc 2025 置信度 0.80
• Natural differential privacy-a perspective on protection guarantees.
  europepmc 2023 置信度 0.80
• SPM-FL: A Federated Learning Privacy Protection Mechanism Based on Local Differential Privacy
  Abstract Federated learning (FL) is a popular distributed machine learning approach that avoids data transfer to third parties by sharing and computing model parameters through a central server, thereby protecting client privacy. However, model weights and oth…
  europepmc Zhiyan Chen, Hong Zheng 2024 置信度 0.80
• Federated parameter-free DBSCAN clustering and its application in image recognition.
  DBSCAN (A Density-Based Algorithm for Discovering Clusters in Spatial Databases with Noise) is a classic clustering algorithm. However, clustering distributed data with privacy protection in edge computing environments is a key challenge for DBSCAN. In this re…
  pubmed Cheng F, Deng Z, Alobaedy MM, Huang X 2026 置信度 0.82
• Differential complication risks in diabetic and non-diabetic geriatric patients following distal femur fracture surgery.
  Current literature is limited regarding the impact of diabetes mellitus (DM) on short- and long-term postoperative complications following distal femur (DF) fracture surgery in geriatric patients. Although DM is a known risk factor for adverse outcomes followi…
  pubmed Tummala S, Mittal MM, Sambandam SN, Sathy A 等 2026 Aug 4 置信度 0.82
• Invasiveness, SOX2 Expression, and Resection Outcomes in TF-Defined PitNETs After Extra-Pseudocapsular Resection.
  To evaluate the associations between transcription factor (TF)-defined molecular lineages and the clinical characteristics of pituitary neuroendocrine tumors (PitNETs).
  pubmed Li XB, Zeng K, Wan XY, Liu HY 等 2026 Aug 3 置信度 0.82
• Markedly improved disease control in Darier disease (ATP2A2-nonsyndromic epidermal differentiation disorder) with ustekinumab versus other biologics: a case series.
  In this case series, we report six patients with severe, treatment-refractory Darier disease, or dyskeratosis follicularis, also known as ATP2A2 -nEDD (nonsyndromic epidermal differentiation disorder), treated with off-label biologic therapy, including dupilum…
  pubmed Skarnvad Andersen A, Baez E, Emmanuel T, Rønholt K 等 2026 Aug 置信度 0.82
• Addressing the Challenges in Using Synthetic Data for Health Research: Application to Cardiology.
  Synthetic data offer significant potential for cardiology research by enabling data sharing, preserving privacy, and supporting machine learning model development. By generating artificial patient records that reflect real-world distributions, synthetic data c…
  pubmed Baschet L, Marque S, Locret S, Jenssen J 等 2026 Jul 31 置信度 0.82
• An artificial intelligence use framework for nursing education: Bridging policy and pedagogical implementation.
  Artificial intelligence (AI) is transforming higher education and healthcare, yet nursing faculty lack practical guidance for determining appropriate AI use in specific academic tasks. Institutional AI policies establish boundaries but rarely address learning …
  pubmed Moore J, Frangieh J, Capello A, Montejo L 等 2026 Jul 30 置信度 0.82
• A 3D PDMS Scaffold Microchip Platform for Non-Invasive Detection of Circulating Endometrial Cells: Revolutionizing Endometriosis Diagnosis.
  To address the urgent need for non-invasive diagnosis of&#xa0; endometriosis, this study developed a novel microfluidic platform utilizing a three-dimensional&#xa0;(3D) polydimethylsiloxane scaffold microchip to efficiently capture circulating endometrial cell…
  pubmed Yang SH, Wang YK, Xu LL, Liu F 等 2026 Jul 30 置信度 0.82
• EffSCG: An Efficient Framework for Real-Time Seismocardiogram Denoising on Resource-Constrained Edge Devices.
  Most deep learning models for wearable devices are still implemented on centralized servers due to memory and computational power limitations under the assumption that these servers will communicate with the wearable units. However, enabling complex physiologi…
  pubmed Emirdagi AR, Yildiz CO, Kilic OS, Cho MJ 等 2026 Jul 29 置信度 0.82
• Age-stratified machine learning using de-identified clinical and transcriptomic data for pediatric appendicitis.
  Pediatric appendicitis triage remains clinically challenging, as standard single-model diagnostic scores yield moderately discriminative performance.
  pubmed Abdullahi SB 2026 Jul 22 置信度 0.82
• Shadow AI in Swedish Health Care: Qualitative Analysis of Physicians' Free-Text Answers.
  The rapid emergence of artificial intelligence (AI) has outpaced its formal adoption in health care organizations, contributing to the emergence of Shadow AI, defined here as the use of unauthorized AI tools by medical professionals. Under the European Union M…
  pubmed Petersson L, Irgang L, Mauritzon I, Holmén M 2026 Jul 28 置信度 0.82
• Tumor-to-tumor metastasis of breast carcinoma to clear cell renal cell carcinoma: a rare case with a review of the literature.
  Tumor-to-tumor metastasis (TTM) is a rare clinicopathological phenomenon in which a malignant tumor metastasizes to another distinct neoplasm. Although renal cell carcinoma (RCC) is a frequent recipient tumor, metastasis from breast carcinoma to RCC is extreme…
  pubmed Nakajima N, Kajiwara H, Okutsu K, Sakemura T 等 2026 Jul 28 置信度 0.82
• The role of machine learning in early detection, accurate diagnosis, and timely treatment of diseases.
  The contemporary healthcare landscape is experiencing a significant transformation driven by the rapid growth of digital health data and advancements in computational technologies. At the center of this evolution is Machine Learning (ML), a branch of artificia…
  pubmed Shrivastava A, Tripathi A, Rajput J 2026 Jul 28 置信度 0.82
• Differential-Privacy-Based Collaborative Protection for Visual and Location Data in UAV Semantic Communications.
  Unmanned aerial vehicle semantic communications are increasingly required in low-altitude sensing, intelligent inspection, and emergency response, where raw image transmission is difficult to sustain under limited onboard resources and time-varying air-to-grou…
  pubmed Yue S, Zhan C, Jiang G, Qiu Y 等 2026 Jul 9 置信度 0.82
• A Color Image Encryption Using a 4D Variable-Order Fractional Hyperchaotic System and Chess-Gameplay-Inspired Dynamic Mechanism.
  With the widespread adoption of digital images in network transmission and storage, the demand for image privacy protection keeps rising. We propose a robust scheme combining a four-dimensional variable-order fractional hyperchaotic system (4D-VOFHS) and a che…
  pubmed Cui X, Zhang X, Ji J 2026 Jul 13 置信度 0.82
• Walking as a Window to the Brain: Redefining Gait in Neurology.
  Walking is not merely locomotion but a window into the nervous system, integrating cortical, subcortical, cerebellar, spinal, and peripheral networks into a unified motor behavior. Across neurological diseases-including Parkinson's disease, atypical parkinsoni…
  pubmed Ortega-Robles E, Treviño M, Manjarrez E, Arias-Carrión O 2026 Jun 23 置信度 0.82
• Mental health damage risk, help-seeking behavior and coping strategies among young college students under different types of network media violence: a comprehensive study based on qualitative phenomenological research methodology.
  With the widespread adoption of network technology and the increasing online engagement among young college students, network media violence has become a prevalent issue threatening their physical and mental health. Different types of network violence exhibit …
  pubmed Gou J, Zhou Q, An L 2026 Jul 21 置信度 0.82
• Enhancing lymph node metastases assessment in breast cancer post-neoadjuvant therapy using artificial intelligence-driven diagnostics.
  Neoadjuvant therapy (NAT) is crucial for locally advanced breast cancer, but post-NAT lymph node assessment is challenging due to histological changes. Current methods like immunohistochemistry (IHC) are labor-intensive and imprecise in distinguishing isolated…
  pubmed Ding Y, Yu J, Liu M, Liu X 等 2026 Jul 21 置信度 0.82
• Privacy-preserving clustered federated learning via differential privacy and homomorphically encrypted prototypes.
  Clustered federated learning (CFL) is an effective paradigm for handling statistical heterogeneity by grouping clients with similar data characteristics and learning cluster-specific models. However, existing CFL methods often expose sensitive clustering signa…
  pubmed Zhan J, Jiang Z, Liu L 2026 Jul 21 置信度 0.82
• Reaching Men and Women Through a Decentralized Mobile Service Delivery Model for HIV Prevention and Pre-Exposure Prophylaxis Services in South Africa.
  Structural and service delivery barriers such as long waiting times, health care provider attitudes, and distance from services prevent access to HIV prevention and pre-exposure prophylaxis (PrEP) services, particularly for young people. The World Health Organ…
  pubmed Nongena P, Martin CE, Muhwava LS, Cholo FA 等 2026 Jul 21 置信度 0.82
• Circulating alpha-1 antitrypsin and its c-terminal peptides differentiate bacterial from viral community-acquired pneumonia.
  Distinguishing bacterial from viral community-acquired pneumonia (CAP) remains a major clinical challenge, often leading to inappropriate antimicrobial use. Alpha-1 antitrypsin (AAT) is an acute-phase protein that regulates neutrophil protease activity and is …
  pubmed Pashai Fakhri M, Börner FR, Held J, Sivaraman K 等 2026 Jul 20 置信度 0.82
• Factors influencing discussion duration in breast cancer multidisciplinary team meetings: insights for streamlining care.
  Multidisciplinary team meetings (MDTMs) in breast cancer care improve outcomes but are time-consuming and costly. This study investigates using data from the Dutch national cancer registry (NCR) and hospital electronic medical records (EMR) to efficiently calc…
  pubmed Kočo L, Sanderink WBG, Prokop M, Mann RM 2026 Jul 20 置信度 0.82
• Federated TinyML and digital twin framework for secure and resilient IoMT-based ICU monitoring.
  Resource-constrained medical sensing devices are increasingly expected to support local intelligence, privacy-preserving collaboration, and secure communication in Internet of Medical Things (IoMT) environments. However, deploying federated learning in ICU mon…
  pubmed Khan UH, Khan R, Alsaedi T, Chelloug SA 等 2026 Jul 19 置信度 0.82
• ViBioChain: a blockchain-enabled architecture for privacy-preserving, ethically governed, and explainable personalized gene editing.
  Personalized gene editing demands robust mechanisms for privacy, ethical governance, and verifiable data integrity. This paper proposes ViBioChain, a modular blockchain-anchored architecture integrating five components: (1)&#xa0;differential chain-of-custody a…
  pubmed Prabakaran C, Kannadasan R 2026 Jul 18 置信度 0.82
• Minimax and adaptive transfer learning for nonparametric classification under distributed differential privacy constraints.
  This paper considers minimax and adaptive transfer learning for nonparametric classification under the posterior drift model with distributed differential privacy constraints. Our study is conducted within a heterogeneous framework, encompassing diverse sample…
  pubmed Auddy A, Cai TT, Chakraborty A 2026 Jul 置信度 0.82
• Federated learning for privacy-preserving multi-center tuberculosis diagnosis using chest imaging data.
  Tuberculosis (TB) remains one of the most serious global health challenges, demanding reliable and early detection methods to reduce transmission and mortality. Chest imaging, particularly chest X-rays, plays a vital role in screening, but its interpretation v…
  pubmed Bhattacharjee S, Sapkal V, Sharma VK, Rewatkar A 等 2026 Jul 置信度 0.82
• Beyond transparency: why Traditional Chinese Medicine (TCM) need explainable artificial intelligence (XAI).
  The integration of artificial intelligence (AI) with Traditional Chinese Medicine (TCM) is rapidly expanding, creating new opportunities for digital diagnosis, syndrome differentiation, prescription recommendation, multimodal clinical support, and knowledge mi…
  pubmed Zheng W, Tong Y, Huang J, Zhu L 等 2026 Jul 14 置信度 0.82
• Beyond the current limits: a novel approach to differentiate small and large intestine in gastroschisis through prenatal imaging.
  This study aims to evaluate the ultrasound differentiation of the fetal extra-abdominal small and large intestines in gastroschisis (GS), analyze their diameters and wall thickness across gestational age in simple (sGS) and complex (cGS) cases, and compare fin…
  pubmed Jaczyńska R, Mikulska B, Rybak-Krzyszkowska M, Mydlak D 等 2026 Jul 14 置信度 0.82
• Decentralized federated distillation for privacy-preserving cross-league basketball data collaboration.
  Cross-league basketball analytics promises richer, more transferable performance models, yet competitive sensitivities and data-protection regulations make raw data sharing across leagues impractical. We propose a decentralized federated distillation framework…
  pubmed Liu S, Guan H, Wang Q 2026 Jul 12 置信度 0.82
• Center-specific Federated Learning for Radiation Pneumonitis: A Cross-Center Adaptive Alternating Framework.
  Accurate prediction of symptomatic radiation pneumonitis (RP) is critical for radiation therapy, however, the generalization of deep learning models is hindered by restricted access to multicenter data. Although federated learning (FL) bypasses data sharing re…
  pubmed Yan M, Wang Z, Ning L, Xuan J 等 2026 Jul 10 置信度 0.82
• Federated deep learning for distributed intrusion detection and privacy preservation in power networks.
  The deepening cyber-physical integration of smart grids has expanded the attack surface of power networks, while centralised intrusion detection schemes struggle with data silos, privacy exposure, and prohibitive communication costs across geographically dispe…
  pubmed Chen L, Tang Z, Yang Y, Xiao X 2026 Jul 9 置信度 0.82
• Predictive fault management in smart sensor networks using a dynamic quantum-AI architecture (DynaQuAI).
  Applications in industrial and smart-infrastructure Wireless sensor networks (WSNs) in the field are increasingly expected to employ predictive intelligence, which, even when operating under dynamic configurations, heterogeneity of hardware, and strong privacy…
  pubmed Alharbi A 2026 Jul 10 置信度 0.82
• A privacy-aware healthcare framework with model pattern-deviation detection for heart-disease prediction using L2-GNAE and PDDP.
  Sensitive patient data protection is essential to ensure medical reliability in healthcare. Yet, the traditional studies didn't analyze the deviation in the shared model pattern, thus resulting in poor diagnosis. Therefore, this article proposes a privacy-awar…
  pubmed Dwivedi R, Kumar B, Mishra V, Hemachandran K 等 2026 Jul 8 置信度 0.82
• Acute gastroenteritis caused by Comamonas testosteroni in a patient with hepatobiliary dysfunction: a case report highlighting diagnostic challenges during the pre-monsoon season in India.
  Comamonas testosteroni is a rare, environmental Gram-negative Bacillus increasingly recognised as an emerging opportunistic pathogen. It is often misidentified as a Pseudomonas species in routine laboratories due to overlapping phenotypic characteristics. Alth…
  pubmed Maheshwarappa YD, Sumana MN, Rao MR, Chitharagi VB 等 2026 Jul 7 置信度 0.82
• NoisyFlow: differentially private optimal transport using neural networks for secure biomedical data sharing across multiple institutions.
  Biomedical models improve when trained on data pooled across institutions, but sensitive patient records (e.g. genomics, clinical data, and medical images) are difficult to share due to privacy constraints. Moreover, data collected at different sites often hav…
  pubmed Li Y, Khandekar N, Wang S, Khanna V 等 2026 Jul 1 置信度 0.82
• Differentially private federated learning for localized control of infectious disease dynamics.
  In times of epidemics, swift reaction is necessary to mitigate epidemic spreading. For this reaction, localized approaches have several advantages, limiting necessary resources and reducing the impact of interventions on a larger scale. However, training a sep…
  pubmed Kerkouche R, Zunker H, Fritz M, Kühn MJ 2026 Jul 6 置信度 0.82
• Economic development and under-five mortality: a global longitudinal analysis of lagged effects and between-country inequalities.
  Understanding the relationship between under-five mortality rate (U5MR) and economic development is essential for promoting global child health and advancing health equity. This study analyzed the spatiotemporal patterns of U5MR and its associations with macro…
  pubmed Li D, An W, Liu B, Qing Z 等 2026 Jul 3 置信度 0.82
• Artificial intelligence in neurovascular surgery: advancing diagnosis, treatment, and outcomes.
  Artificial intelligence (AI) is transforming neurovascular surgery by improving diagnostic accuracy, risk prediction, treatment planning, and patient outcomes. This narrative review examines AI across the continuum of cerebrovascular care, from initial diagnos…
  pubmed Li L, Zhang Z, Zong L 2026 置信度 0.82
• BlockFedMed: A blockchain-federated learning framework for privacy-preserving mortality prediction across heterogeneous intensive care units.
  Electronic health records are distributed across different hospitals that work on powerful AI models but cannot be shared due to HIPAA and GDPR regulations. Federated learning (FL) avoids raw data sharing, yet lacks tamper-evident consent governance, adversari…
  pubmed Yadav AK, Deshmukh M 2026 Jun 27 置信度 0.82
• AI Privacy and Security in Healthcare: A Systematic Literature Review.
  Artificial intelligence is expanding into telemedicine and telerehabilitation, yet significant privacy and security concerns persist.
  pubmed Dolezel D, Lalani K, Watzlaf V, Butler-Henderson K 等 2026 置信度 0.82
• AI in Genomics: From Variant Calling to Multi-Omics Integration.
  Artificial intelligence (AI) strategies are revolutionizing genomics by extracting complex patterns that traditional statistical pipelines are likely to miss. This mini-review aims to provide a concise overview of how AI is transforming major genomic technolog…
  pubmed Sultana H, Mohanty S, Solomon AD, Iqbal MY 等 2026 Jul 置信度 0.82
• "It Reduces Stigma Now That the Service Is Under One Roof" Women and Provider Experiences on Factors Influencing Effective Integration of Oral PrEP Delivery in Family Planning Clinics in Kenya: A Qualitative Study.
  Women of childbearing age in sub-Saharan Africa continue to face a disproportionately high risk of HIV acquisition. Integrating pre-exposure prophylaxis (PrEP) into existing care platforms such as family planning (FP) services may offer a strategic opportunity…
  pubmed Ogello V, Ngure K, Mutai S, Awuor M 等 2026 Jul 置信度 0.82
• RiskSetDP: session-level differential privacy for survival analysis with risk-set-aware sensitivity control.
  Real-world survival analysis rarely ends with a single deliverable: practitioners typically publish cohort-level statistics, a deployable time-to-event model, interpretable Kaplan-Meier curves, and, where appropriate, a synthetic table for secondary use. When …
  pubmed Ou Z, Luo Z, Duan W, Xiao Z 等 2026 Jul 1 置信度 0.82
• The scope of physiotherapy in men's health: a qualitative study on clinician experiences.
  Men's health physiotherapy is an expanding subspecialty that addresses pelvic floor dysfunction, sexual health disorders, and chronic pelvic pain in men. However, practitioners' perspectives remain underexplored, particularly in healthcare contexts where refer…
  pubmed Erkut U, Önal B, Unes S 2026 Jul 1 置信度 0.82
• The profiles of vaginal microbiota in fertile and infertile Thai women.
  Vaginal microbiota dysbiosis has been associated with female reproductive health and infertility. This study aimed to compare vaginal microbiota profiles according to fertility and ovarian induction status among Thai women.
  pubmed Li J, Apinuthirunchot T, Chaithongwongwatthana S, Chanchaem P 等 2026 Jun 30 置信度 0.82
• Chaos-driven design of highly nonlinear S-boxes for secure and efficient lightweight image encryption.
  Substitution boxes (S-boxes) are a type of nonlinear component which provides confusion and robustness to cryptanalysis in modern symmetric ciphers. Due to the requirements of lightweight encryption (LWE) systems to achieve a high degree of security while mini…
  pubmed Said L, Alshammari FS, Khan M 2026 Jul 1 置信度 0.82
• Classification Under Local Differential Privacy with Model Reversal and Model Averaging.
  Local differential privacy (LDP) has become a central topic in data privacy research, offering strong privacy guarantees by perturbing user data at the source and removing the need for a trusted curator. However, the noise introduced by LDP often significantly…
  pubmed Qin C, Bai Y 2026 置信度 0.82
• microRNA-204 as a crucial cancer stem cell related miRNA inhibits stemness of gastric cancer by targeting CD44 and EPCAM.
  Cancer stem cells (CSCs) and normal stem cells share key properties such as self-renewal and differentiation capacity, yet the microRNAs (miRNAs) that are differentially expressed between them remain poorly characterized. This study aimed to identify such miRN…
  pubmed Li D, Zhou R, Cheng Z, Xu H 等 2026 Jun 30 置信度 0.82
• BC-AWFedAvg: blockchain-assisted adaptive federated learning for secure RAN Slicing in beyond-5G networks.
  The evolution of beyond-5G networks introduces new challenges for radio resource management, particularly for heterogeneous service requirements across multiple virtual network operators. This work presents BC-AWFedAvg, a layered framework for federated deep r…
  pubmed Zemzemi M, Hajlaoui JE, Aldalbahi AS, Mhatli S 2026 Jun 29 置信度 0.82
• A federated digital twin reveals cytomegalovirus reactivation impairs CAR-T cell therapy via IL-15-mediated cytokine competition in B-Cell lymphoma.
  Cytomegalovirus (CMV) reactivation occurs in 30 - 40 % of seropositive patients receiving chimeric antigen receptor T-cell (CAR-T) therapy for B-cell lymphoma and is strongly associated with treatment failure. However, the causal immunological mechanism drivin…
  pubmed Sridharan P, Ghosh M 2026 置信度 0.82
• CBINN: Cancer Biology-Informed Neural Network for Unknown Parameter Estimation and Missing Physics Identification.
  The dynamics of tumor-immune interactions within a complex tumor microenvironment are typically modeled using a system of ordinary differential equations or partial differential equations. These models introduce some unknown parameters that need to be estimate…
  pubmed Chhetri B, Kumar BVR 2026 Jun 27 置信度 0.82
• How do mature non-graduate students compare to the rest of the cohort in medical training? A UKMED study.
  Widening participation in medicine is a key societal priority. To improve representation of non-traditional applicants, UK medical schools use contextual admissions, although definitions of under-represented groups vary across institutions. This study examined…
  pubmed Sartania N, Troughton A, Chan P 2026 Jun 26 置信度 0.82
• A quantum resistant chaos driven image encryption framework for secure visual data transmission in intelligent transportation systems.
  The use of image-sensing and real-time processing in Intelligent Transportation Systems (ITS) has introduced a sudden surge in transmitting and gathering high-resolution visual data from vehicle cameras, road infrastructures, and user devices. Such image data …
  pubmed Prajwalasimha SN, Sharma A, Saini DKJB, Rai BK 等 2026 Jun 26 置信度 0.82
• An Integrated IoT-Based Multi-Sensor Framework for Real-Time Indoor Environment and Safety Monitoring.
  Poor indoor air quality, inadequate ventilation, and unnoticed local disturbances can reduce occupant well-being and compromise practical safety in smart-home and small-building environments. Although low-cost Internet-of-Things (IoT) sensing technologies are …
  pubmed Naing AM, Al-Hamid DZ, Singh A 2026 Jun 10 置信度 0.82
• DAG-CTFL: DAG Blockchain Cross-Layer Authentication Framework for Trustworthy IoV Federated Learning.
  Privacy-preserving federated learning in the internet of vehicles (IoV) requires low-latency authentication, bounded privacy leakage, and robustness against malicious model updates. However, most existing studies separately design communication authentication …
  pubmed Liao L, Chen L 2026 May 26 置信度 0.82
• Privacy-Enhanced Vertical Federated Learning for Healthcare via Directional Noise and Subset Representations.
  Vertical federated learning (VFL) allows healthcare institutions to train models on complementary patient features without sharing raw data, but strong differential privacy often causes severe utility loss and labeled medical data are limited.We propose HEAL, …
  pubmed Wang Q, Dai M, Wu C 2026 Jun 25 置信度 0.82
• Converting a Cough Counter into a Cough Monitor: A Way Forward?
  Background/Objective : To identify respiratory pathology, automated cough counting is frequently proposed. A trial validating an early warning system for exacerbations in chronic obstructive pulmonary disease (COPD) patients was recently concluded successfully…
  pubmed Brinker ACD, Crooks MG, Morice AH 2026 Jun 17 置信度 0.82