Primary Care

AI-assisted literature screening: A hybrid approach using large language models and retrieval-augmented generation.

OBJECTIVE: Current systematic literature reviews largely rely on manual screening of articles retrieved through keyword search, which is time-consuming and difficult to scale. To address this limitation, large language model (LLM)-based approaches offer the potential to automate the screening process. In this study, we aim to enhance the efficiency and accuracy of literature screening by developin...

GCLM as a novel biomarker for preeclampsia: Integrating bioinformatics and mechanistic validation.

INTRODUCTION: Preeclampsia (PE) is a pregnancy-specific disorder associated with hypertension and multi-organ dysfunction, posing serious risks to maternal and fetal health. Early detection remains challenging, highlighting the urgent need to identify reliable molecular biomarkers for improved diagnosis and therapeutic intervention. METHODS: We integrated Gene Expression Omnibus (GEO) datasets (GS...

Screening tools and strategies for early detection of oral cancer and potentially malignant disorders in rural and low-resource populations: A systematic review.

Oral cancer and its precursor lesions, known as oral potentially malignant disorders (OPMDs), present significant public health challenges due to high...

Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.

Type 2 diabetes is a polygenic, heterogeneous disease affecting over 530 million individuals worldwide, a number projected to rise to 1.3 billion by 2...

C-peptide Index under Non-fasting Conditions Can Predict the Likelihood of Future Insulin Therapy in Outpatients with Type 2 Diabetes Mellitus Not Receiving Insulin at Baseline.

Objective This study aimed to develop a clinical model in which the C-peptide index (CPI) under non-fasting conditions can predict future insulin ther...

Molecular targeted therapies, omics, and AI based theranostics approaches for the treatment of prostate cancer.

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells, some of which can spread and migrate to other tis...

Cancer as a main contributor to multimorbidity in the UK Biobank: analysis of risk factors using conventional statistical modelling and machine learning.

Cancer frequently co-occurs with other chronic conditions, contributing substantially to disease burden. Multimorbidity is an increasing public health...

The use of machine learning to predict pharmacological therapy in gestational diabetes: A scoping review.

AIMS: Early identification of pharmacological therapy for gestational diabetes mellitus (GDM), a common pregnancy complication, through machine learni...

Diverse combination of factors associated with the development of diabetic kidney disease among data-driven diabetes subtypes: analysis of the J-DREAMS registry.

AIMS/HYPOTHESIS: Available methods for predicting the onset and progression of diabetic kidney disease (DKD) and end-stage kidney disease (ESKD) are n...

Deep learning-based obstructive coronary artery disease prediction from myocardial perfusion SPECT.

PURPOSE: We aim to apply the deep learning (DL) technique to predict the gold-standard invasive coronary angiography (ICA) for coronary artery disease...

Artificial intelligence-driven clinical decision support systems to assist healthcare professionals and people with diabetes in Europe at the point of care: a Delphi-based consensus roadmap.

The use of artificial intelligence (AI) to improve the diagnosis, assessment and treatment of people with diabetes has the potential to drive a paradi...

Colonoscopy Quality and Strategies for Improvement.

Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and mortality. Its effectiveness depends on colonoscop...

Depression screening with textual and audio features based on large language models and machine learning.

BACKGROUND: Depression is a complex disorder that cannot be fully screened by textual features alone, as audio features capture additional psychomotor...

Compact large language models for title and abstract screening in systematic reviews: An assessment of feasibility, accuracy, and workload reduction.

Systematic reviews play a critical role in evidence-based research but are labor-intensive, especially during title and abstract screening. Compact la...

Machine learning-assisted high-performance immunoSERS platform using silk fibroin as a natural etching mask for early diagnosis of Alzheimer's disease.

Early and accurate diagnosis of Alzheimer's disease (AD) is a major stride toward pharmacological interventions to delay the onset or progression of t...

Manipulating starch crystalline structure for controlled digestibility and glycemic response.

Postprandial hyperglycemia is a key driver in the development of type 2 diabetes, and dietary starch is a major modulator of glycemic response. The cr...

Special AAO Report: Recommendations on Screening for Hydroxychloroquine Retinopathy (2025 Revision).

BACKGROUND: The American Academy of Ophthalmology recommendations on screening for hydroxychloroquine (HCQ) retinopathy are now a decade old. This rev...

Machine Learning-Based Risk Prediction for Feline Mammary Tumours: A Comprehensive Epidemiological Analysis Using Multi-Model Ensemble Approach.

Feline mammary tumours represent the third most common malignancy in cats, with limited evidence-based tools available for risk assessment and screeni...

Association of HbA1c and an updated glucose management indicator (uGMI) with incident diabetic retinopathy in adults with type 1 diabetes: a longitudinal study.

AIMS/HYPOTHESIS: This study aimed to compare the predictive performance of HbA1c and a continuous glucose monitoring (CGM)-based updated glucose manag...

Artificial intelligence-powered signal analysis of loop-mediated isothermal amplification (LAMP) for the screening of Kaposi sarcoma at the point of care.

Unlike the polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP) lacks a consistent thermal cycle, making quantification part...