Primary Care

Using full agreement across multiple large language models for title-and-abstract screening in systematic reviews: a proof-of-concept.

BACKGROUND: The exponential growth of scientific literature poses significant challenges for conducting systematic reviews, particularly in the labor-intensive title-and-abstract screening phase. This study examines the feasibility of using multiple large language models (LLMs) for title-and-abstract screening in systematic reviews. METHODS: We propose and evaluate a full-agreement approach using ...

Engagement with an AI- and CGM-Integrated Digital Health Platform Is Associated with Clinically Significant Weight Loss.

BACKGROUND: Obesity affects millions of U.S. adults and is linked to cardiometabolic disease. This study examined whether user engagement with the Signos app, which combines artificial intelligence (AI) and continuous glucose monitoring (CGM), is associated with weight loss. METHODS: This study included adults (≥18 years) with BMI ≥ 30 kg/m2 and without diabetes who enrolled in the Signos System, ...

Diagnosing helminth infections in a large reference laboratory in the United States: a 6-month pre- and post-implementation analysis of AI-augmented screening of concentrated fecal wet mounts.

Helminth infections are uncommon in the United States, yet accurate detection remains critical. Conventional ova-and-parasite examinations are labor-i...

Cell-specific multi-target mechanisms of cotinine in cervical cancer oncogenesis and progression.

BACKGROUND: Cervical cancer is the fourth most common malignant tumor in women globally, with tobacco smoke being a major environmental risk factor. T...

Advances in diabetes technology: clinical implications, limitations, and future perspectives.

Diabetes technology has transformed substantially over the past two decades, becoming central to modern diabetes management. Continuous glucose monito...

Artificial Intelligence in Self-Management of Gestational Diabetes Mellitus: A Systematic Review.

The prevalence of gestational diabetes mellitus (GDM) continues to rise, necessitating reliable and effective self-management strategies to improve ma...

Embodied Intelligence Applications in Health Care Populations: Scoping Review.

BACKGROUND: Embodied intelligence-artificial intelligence instantiated in physical or virtual bodies that can perceive, communicate, and interact with...

Opportunistic Screening Based on Computed Tomography in Musculoskeletal Radiology: How and Why.

With the rapid growth of the use of computed tomography, advances in artificial intelligence enable opportunistic screening, the systematic extraction...

Comparison of ChatGPT and dietitians in formulating diet plans and recommendations for patients with cardiometabolic diseases.

BACKGROUND: Artificial Intelligence (AI) is transforming personalized medicine, yet its efficacy constitutes a dynamic factor in the field of health a...

DeepAdapter: a generalisable algorithm integrating self-supervised learning and unsupervised domain adaptation for robust retinopathy of prematurity screening.

AIMS: To develop and validate DeepAdapter, a novel deep learning algorithm that integrates self-supervised learning (SSL) and unsupervised domain adap...

Novel method for risk stratification of radiation-induced breast fibrosis: subgroup hypothesis verified by machine learning.

Breast fibrosis (BF) after radiotherapy remains one of the most dreaded late toxicities in breast cancer care, yet multiple additive predictors strugg...

AI-driven discovery of synergistic combinations from Psoralea corylifolia fruit for treating osteoporosis.

BACKGROUND: Estrogen-deficient osteoporosis demands safe and effective therapies. Psoralea corylifolia fruit (PCF), a phytoestrogenic herbal medicine ...

A methodological framework for integrating generalisable deep learning and radiomics fusion model for early lung cancer detection across multi-centre imaging datasets.

Early detection of lung cancer remains one of the most effective strategies for improving survival; however, diagnostic performance is limited by vari...

A Machine Learning Approach to Voice-Based Parkinson Disease Screening Using Multiview Spectrogram and Speech Recognition Features: Diagnostic Study.

BACKGROUND: Parkinson disease frequently manifests early vocal impairment, motivating the development of noninvasive and scalable digital screening to...

AI-Enhanced Point-of-Care Diagnostics for Infectious Diseases in Resource-Limited Settings: A Scoping Review.

OBJECTIVES: To systematically map the extent and nature of research on AI-enhanced point-of-care (POC) and rapid diagnostic technologies for infectiou...

Swin-DRNet: A robust transformer framework for diabetic retinopathy screening under heterogeneous imaging conditions.

Diabetic retinopathy (DR) has been known as one of the leading preventable causes of vision impairment globally and requires automated screening syste...

Transcriptomic analysis identifies novel ferroptosis-related biomarkers and therapeutic targets in pulmonary arterial hypertension.

BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes...

Head-to-Head Comparative Evaluation of Four Commercially Available Artificial Intelligence Systems for Detecting Referable Diabetic Retinopathy in a Tanzanian Population.

OBJECTIVE: Comparative evaluations of commercially available artificial intelligence (AI) systems for use in diabetic retinopathy (DR) screening, part...

Identifying PLAU as a shared pathogenic gene in type 2 diabetes and bladder urothelial carcinoma through integrated transcriptomic analysis and machine learning for diagnostic and therapeutic value.

Type 2 diabetes mellitus (T2DM) and bladder urothelial carcinoma (BLCA) are two kinds of diseases that seriously threaten human health. Their pathogen...

Development and validation of a machine learning-based model for predicting delirium risk in postoperative brain tumor patients in the Intensive Care Unit.

OBJECTIVE: This study aimed to clarify the incidence and influencing factors of delirium in ICU patients after brain tumor surgery, construct and vali...