Primary Care

Large language models show promising performance for some systematic review tasks but call for cautious implementation : a systematic review.

OBJECTIVES: With the exponential growth of biomedical literature, the challenge of conducting systematic reviews is becoming increasingly burdensome. We aimed to evaluate the performance of LLMs in the automation of some or all steps of systematic reviews and meta-analyses. STUDY DESIGN AND SETTING: In this systematic review, we searched PubMed, Embase, the Cochrane Library and preprint platforms ...

Real world practice of Artificial intelligence Diagnostic System for Diabetic Retinopathy in Taiwan.

PURPOSE: We evaluated the alterations of applying artificial intelligence (AI) diagnostic system for diabetic retinopathy (DR) screening in real-world practice. METHODS: This retrospective study included 11,713 diabetic patients from the government-led Diabetes Shared Care Network. The AI system Verisee was integrated into the clinical workflow to identify referable diabetic retinopathy (RDR). Its...

Identifying serum amino acid as biomarkers of gestational diabetes mellitus in second-trimester among Chinese pregnant women: a machine learning-based cross-sectional study.

BACKGROUND: Levels of plasma branched-chain and aromatic amino acids in pregnancy have been associated with gestational diabetes mellitus (GDM), but t...

Computer-aided structural modeling and drug discovery for G-protein-coupled receptors in the age of artificial intelligence.

G-protein-coupled receptors (GPCRs) are a large family of membrane proteins that mediate cellular responses to diverse stimuli and serve as targets fo...

Analysis and prediction of cardiovascular research hotspots, trends and interdisciplinarity.

OBJECTIVE: Comprehensive data and analyses on cardiovascular research could clarify recent research trends for the academic community and facilitate p...

Machine-Learning-Assisted Screening of Electrolyte Additives for Aqueous Zinc-Ion Batteries via a Molecular Descriptor Framework.

Additive engineering in aqueous zinc-ion batteries is recognized as a key strategy for improving zinc anode stability. Nevertheless, the conventional ...

Glucose Predictions Improve Glycemic Control: A Digital Twin Evaluation.

BACKGROUND: Glucose predictions aim to empower continuous glucose monitoring (CGM) users by enabling preventive actions to reduce adverse glycemic eve...

Digital Health Solutions for Type 2 Diabetes and Prediabetes: Systematic Review of Engagement Barriers, Facilitators, and Outcomes.

BACKGROUND: Digital health interventions, including artificial intelligence (AI)-driven solutions, offer promise for type 2 diabetes mellitus (T2DM) a...

Complete Blood Count-Derived Inflammation Indices to Predict 3-Year All-Cause Mortality in Patients With Diabetes and Acute Myocardial Infarction in Critical Care: Retrospective Cohort Study With Single-Center External Validation.

BACKGROUND: Inflammation plays a pivotal role in the progression of diabetes and its cardiovascular complications, particularly acute myocardial infar...

[Annual progress in critical care of pulmonary medicine 2025].

This review systematically summarizes the annual research advances in the field of critical care of pulmonary, with a focus on pulmonary and critical ...

Towards the future of Endocrine Laboratory Medicine: defining the role of laboratory medicine specialists to strengthen the clinical-biological partnership - a joint opinion paper of EFLM-C:YS, IFCC TF-YS, and ESE-EYES.

Clinical endocrinology relies critically on high-quality biochemical data for diagnosis, therapeutic decisions, and long-term patient monitoring. As e...

Mathematical modelling and analysis of human metapneumovirus transmission dynamics using neural network intelligence and optimal control.

Human metapneumovirus (hMPV) is a serious global health threat because it causes human respiratory diseases in people of all ages. The complicated dyn...

Prostate Cancer Screening in the MR Imaging Era: Evidence, Strategies, and Future Directions.

Prostate cancer screening has entered a new era with the integration of MR imaging and artificial intelligence (AI) into diagnostic workflows. This pa...

Do Commercial Airline Policies for Passengers With Obesity Carry Enough Weight?

INTRODUCTION: The travel industry has a responsibility to accommodate the needs of all its customers, including those with obesity. It is not known to...

Validation of the Eyerobo FC Portable Fundus Camera for Diabetic Retinopathy Screening Using Public Datasets and Deep Learning.

INTRODUCTION: To validate the diagnostic performance of the Eyerobo FC, a new portable non-mydriatic fundus camera for diabetic retinopathy (DR) scree...

Guiding Preventive Care Strategies for Patients With Atherosclerotic Plaque on Coronary CTA: Primary Outcomes of the DECIDE Registry.

BACKGROUND: Artificial intelligence-enabled coronary plaque analysis (AI-CPA) has been shown to improve cardiovascular risk prediction. However, littl...

Silent Signals: The Expanding Role of Cell-Free DNA in Women's Health, Pregnancy, and Reproductive Medicine.

Cell-free DNA (cfDNA) is an emerging biomarker detectable in various bodily fluids, with promising implications across a wide range of clinical domain...

An automated framework for quantitative alveolar bone loss using deep learning-based landmark detection.

OBJECTIVE: To develop and evaluate an automated framework for full-mouth quantification of radiographic alveolar bone loss (ABL) on panoramic radiogra...

Latent Supervision: A Method for Improved Performance and Calibration of Machine Learning Classification Models in Ophthalmology.

PURPOSE: Standard supervised learning assumes deterministic labels (e.g., positive or negative, present or absent), neglecting the diagnostic uncertai...

Glucose forecasting and hypoglycemia forewarning in type 1 and type 2 diabetes using deep learning.

Hypoglycemia is a major barrier to safe diabetes management. Although deep learning has been widely applied to blood glucose (BG) prediction, most stu...