FDA General

The Continuity Trap in Data Science Health Research.

Secondary use is now the ordinary condition of data science health research rather than an exception to it. Electronic health records collected for clinical care become prediction tools and inputs for generative AI; imaging archives become foundation-model corpora; genomic datasets become resources for polygenic risk scores; and legacy biospecimens become renewable, indefinitely distributable cell...

Artificial intelligence agents and agentic artificial intelligence applied to precision medicine.

Precision medicine seeks to individualise care by integrating multimodal biomedical data, yet most deployed clinical artificial intelligence (AI) remains assistive, providing predictions without managing workflows or adapting autonomously. Agentic AI, built on large language models (LLMs), has emerged as a paradigm characterised by autonomy, goal-directed reasoning, memory, planning and tool use. ...

A Governance Framework for Diagnostic Quality in Hospital-Radiology Joint Ventures.

RATIONALE AND OBJECTIVES: Hospital-radiology joint ventures (JVs) are forming at an accelerating pace as health systems seek to recapture outpatient i...

1,357 AI medical devices cleared, 3 actually tested on patient outcomes.

Artificial intelligence (AI) tools are entering clinical practice at unprecedented speed. 1,357 AI/ML-enabled medical devices have received U.S. FDA c...

Microbiome-Driven Precision Medicine in Asthma: Roles of Targeted Therapies and Artificial Intelligence.

OBJECTIVE: To evaluate the current evidence regarding airway and gut microbiome alterations in asthma pathogenesis and therapeutic response, and to ex...

Placenta-derived Exosomes Mitigate Hypoxia-Induced Trophoblast Apoptosis and Inflammatory Progression via SASH1.

SASH1 is a signal adaptor protein involved in cell growth, apoptosis, and immune regulation, and has been increasingly studied in tumor and immune cel...

Subtyping and Prediction of the Glucose Based on the Hybrid Modeling of Deep Learning and Dietary Stimulated Glucose Metabolism Dynamical Model.

Diabetes represents a significant global health challenge, underscoring the need for enhanced methodologies in glycemic monitoring and risk assessment...

Cost-Effectiveness of an Artificial Intelligence as a Medical Device (AIaMD) for Triaging Patients Presenting to Primary Care with Concerns that They Have a Skin Cancer: A Modelling Study.

INTRODUCTION: Health services are struggling to cope with the growing numbers of people coming with skin lesions they are worried could be cancer. Usi...

HRV-anchored autonomic-morphological structured factorization for interpretable multimodal cardiovascular risk prediction.

Cardiovascular risk prediction from heterogeneous physiological signals supports early warning in bedside and wearable monitoring, where ECG, PPG, HRV...

Deep-Learning Based Contrast Boosting: A Multi-Center Multi-Reader Study on Clinical Performance With Standard Contrast Enhanced Brain MRI.

BACKGROUND: Gadolinium-based contrast agents are used in brain MRI to improve the visualization of disorders and improve the delineation of lesions. H...

Structure- and deep learning-guided engineering of a size-minimized CRISPR/Cas.

Multidomain proteins play central roles in cellular regulation, yet their intrinsic flexibility and structural instability often hinder optimization f...

The INTREPID program: Linking illicit fentanyl-containing tablets and powders seized at US borders to a common origin by combining physical/chemical identifiers and machine learning.

Three US government agencies, the Drug Enforcement Administration (DEA), Customs and Border Protection (CBP), and Food and Drug Administration (FDA), ...

Large language models and prostate MRI reporting: a stringent testbed for safe deployment under evolving AI, health-data, and cybersecurity regulation.

Prostate magnetic resonance imaging (MRI) reporting is a high-impact communication task because small differences in lesion laterality, sector localiz...

The miRNA-virus Axis in RNA Virus Infections: Mechanisms, Therapeutic Targeting, and Systems Biology Approaches.

RNA viruses are a diverse and rapidly evolving group of pathogens that significantly contribute to worldwide morbidity and mortality, propelled by ele...

Development and clinical validation of a point-of-care cytology screening tool for oral potentially malignant disorders and oral squamous cell carcinoma using a deep learning convolutional neural network: protocol for a diagnostic accuracy study.

INTRODUCTION: Oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) present a remarkable public health challenge worldw...

Cross-Species Generalization and Comparative Performance Analysis of Deep Neural Network Architectures in Histological Image Classification.

Histological image classification plays a critical role in biomedical research and diagnostic processes. Advances in the field of deep learning presen...

From Collapse to Active Self-Repair: Integrative Multi-Omics and Machine Learning Analysis Map the Hepatic Metabolic Adaption in Response to Simulated Spaceflight Stress.

Long-term spaceflight poses substantial challenges to human physiology, with the liver being highly susceptible due to its central metabolic role. To ...

[(DGH) Digitalisation in Hand Surgery - A Survey on the Current Situation among Members of the German Society for Hand Surgery (DGH)].

BACKGROUND: Digitalisation, and in particular the use of artificial intelligence (AI), is becoming increasingly important in medicine. At the same tim...

Identifying candidate therapeutic targets in amyotrophic lateral sclerosis through a transcriptome-wide machine-learning consensus approach for drug repurposing.

Amyotrophic lateral sclerosis (ALS) is a heterogeneous neurodegenerative disease for which effective disease-modifying therapies remain limited. This ...

GPCR Biology-Informed Drug Discovery in Asthma.

Advances in GPCR biology and drug-discovery technology are simultaneously reshaping what can be targeted in asthma and how those strategies must be va...