Preventive Care

An Umbrella Review of Artificial Intelligence Applications in Mental Health Care.

BACKGROUND: Artificial intelligence (AI) is increasingly used in mental health care to address rising demand, workforce shortages and access barriers; however, evidence remains scattered across multiple systematic reviews, limiting synthesis and practical application. OBJECTIVE: To synthesise evidence on AI applications in mental health care, including trends, uses, benefits, challenges and risk-m...

Artificial intelligence (AI)-enabled platforms for cancer vaccine engineering.

Cancer vaccines are emerging as a promising approach in immuno-oncology, with the potential to generate tumour-specific and long-lasting immune responses. However, shared-antigen strategies often show limited efficacy because of tumour heterogeneity, immune escape and challenges in identifying immunogenic targets, ultimately limiting progress towards effective immunotherapies. Recent breakthroughs...

Current State and Impact of Implementation of In-Silico Tools in the Biopharmaceutical Industry - Proceedings of the 6th Modeling Workshop.

The sixth modeling workshop (6MW) was held in June 2025 at Collegeville, Pennsylvania, USA, and supported by the Recovery of Biological Products Confe...

Pre-pandemic preventive healthcare engagement and all-cause excess mortality during COVID-19: a county-level ecological study in the United States.

OBJECTIVE: Community resilience during COVID-19 has been linked to social conditions, public-health capacity, and acute-care resources, but the contri...

Proof of Concept of Large Language Models for Opioid Treatment Policy Surveillance: 97% Agreement With Subject Matter Experts.

OBJECTIVE: Policy surveillance typically involves detailed, time-consuming manual screening of policies for inclusion in a final dataset. This screeni...

Grading-labour cost analysis of AI-assisted versus human-only diabetic retinopathy screening in two Danish healthcare settings.

PURPOSE: Diabetic retinopathy (DR) screening is essential to prevent vision loss, yet rising diabetes prevalence threatens to outpace ophthalmology ca...

Neoantigen in cancer immunotherapy: mechanism, therapeutic strategies and future perspectives.

Neoantigens are tumor-specific antigens resulting from genetic, transcriptomic, and proteomic changes, making them a promising avenue for personalized...

Machine learning for precision obstetrics: A comprehensive review of risk prediction models for hypertensive disorders and pregnancy-related syndromes.

Gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), preterm birth, and intrauterine growth restriction represent major con...

Perception and accuracy of an AI-based contactless wellness screening system in dental setting; a cross-sectional study.

This study evaluates the reliability and participants' responses to a contactless artificial intelligence (AI) device powered by Remote Photoplethysmo...

Applications of artificial intelligence in rural ophthalmology: a scoping review.

OBJECTIVE: Artificial intelligence (AI) is increasingly utilized for screening within ophthalmology, yet its application in rural communities remains ...

The association between serum chloride levels and asthma prevalence: A cross-sectional study with variable screening and validation guided by machine learning.

Prior evidence suggests that ion channel dysfunction plays a significant role in the pathogenesis of asthma, which provides a theoretical basis for th...

Temporal shifts in public perceptions of influenza and its vaccine before, during, and after COVID-19 in a fragile nation.

BACKGROUND: Since the emergence of the COVID-19 pandemic, co-infection with COVID-19 and influenza has been associated with adverse health and economi...

AI-assisted second forward-view examination of the right colon significantly improves the adenoma detection rate: a multicenter randomized controlled trial.

BACKGROUND: Adenomas in the right colon are likely to be missed during colonoscopy because of anatomical complexity and lesion characteristics. Althou...

Artificial intelligence in diabetic retinopathy: from automated screening to risk-stratified care.

Diabetic retinopathy (DR) is a leading cause of preventable blindness worldwide. The rising prevalence of diabetes has strained conventional screening...

Demographic Confounding in Voice-Based Parkinson Disease Screening: Methodological Analysis of the Bridge2AI Voice Dataset.

BACKGROUND: Voice-based deep learning models for Parkinson disease (PD) and dementia screening report areas under the curve (AUCs) of 0.85-0.97, but r...

Performance of Two AI Approaches in ASReview Compared With Manual Screening for Dementia Care Literature Screening: Comparative Analysis.

BACKGROUND: Literature reviews rely on rigorous title and abstract screening by researchers, which is time-consuming. AI-assisted literature screening...

Outcomes of Single-View Asymmetries Recalled From Screening Mammography and Exploratory Analysis of AI Detection.

PURPOSE: To evaluate the diagnostic outcomes of single-view asymmetries (SVAs) recalled from screening mammography and to explore the association betw...

AI-Assisted Line-Field Confocal Optical Coherence Tomography to Detect Subclinical Basal Cell Carcinoma.

IMPORTANCE: Basal cell carcinoma (BCC) is the most common type of skin cancer worldwide. Particularly on the face, its locally destructive growth lead...

Keeping the endoscopist in the loop: can artificial intelligence improve colonoscopy without deskilling endoscopists?

Artificial Intelligence Analysis of Standard 12-Lead Electrocardiograms for Screening of Symptomatic Diabetic Peripheral Neuropathy.

AIM: To investigate whether artificial intelligence (AI) models trained on standard 12-lead electrocardiograms (ECG) can identify symptom-defined diab...