Primary Care

Using Large Language Models to Determine Reasons for Missed Colon Cancer Screening Follow-Up.

BACKGROUND: Identifying reasons for missed preventive care, such as follow-up colonoscopy after an abnormal stool-based colon cancer screening test, is critical for quality improvement initiatives. However, manual chart review is time-consuming and costly. This study serves as a proof-of-concept demonstration of using large language models (LLMs) to automate the identification of documented reason...

AI-based classification of pediatric sagittal skeletal patterns using multi-view facial photographs.

OBJECTIVE: The increasing global demand to assess pediatric skeletal malocclusions poses a growing challenge, as current screening methods are dependent on availability of orthodontists and X-rays, which limits accessibility. This study aimed to develop and validate an artificial intelligence (AI) model based on facial photographs to predict pediatric sagittal skeletal pattern classifications and ...

Analysis of B-Scan Ultrasonography Using Neural Networks to Predict Risk of Fibrosis in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD).

OBJECTIVE: The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) continues to rise, underscoring the need for tools to st...

Accuracy of ChatGPT, Gemini, Claude and DeepSeek in Carbohydrate Counting.

AIMS: To evaluate the accuracy of four general-purpose artificial intelligence (AI) models-ChatGPT (OpenAI), Gemini (Google), Claude (Anthropic) and D...

Unsupervised phenotyping of the periodontal architecture through high-dimensional clustering of electronic health records: A multicenter study.

BACKGROUND: To identify novel periodontal phenotypes using unsupervised machine learning on a large-scale, multicenter cohort, specifically characteri...

An interpretable machine learning tool for rheumatoid arthritis screening: integrating novel cellular morphological parameters with routine blood count indices.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease that can cause significant disability. Early detection is vital for improving ou...

Cost-effectiveness of AI-enhanced breast cancer screening in Iran: a microsimulation study.

BACKGROUND: Recognized worldwide as a major health threat and Sustainable Development Goal priority, breast cancer places an especially heavy clinical...

Web-Based Personalized Machine Learning Recommendations to Enhance Shared Decision-Making in Prostate-Specific Antigen Screening: Randomized Controlled Trial.

BACKGROUND: Prostate‑specific antigen (PSA) screening involves complex trade‑offs between early detection and the risks of overdiagnosis. For older ad...

Diabetes Technology: An Update.

Diabetes is one of the most prevalent chronic diseases worldwide, with rates that continue to increase. Over 30 years ago, the Diabetes Control and Co...

Performance of Machine Learning Models for Sepsis and Stroke Detection Using EMS Data.

OBJECTIVES: Early sepsis and stroke recognition by emergency medical services (EMS) improves triage, treatment, and patient outcomes. Machine learning...

Using Machine Learning to Improve Screening for Oropharyngeal Dysphagia in Hospitalized Versus Primary Care Adult Patients With COVID-19 Disease: Retrospective Observational Study.

BACKGROUND: Oropharyngeal dysphagia (OD) commonly occurs in patients with COVID-19 disease, posing diagnostic challenges due to isolation protocols. O...

Development and Validation of a Web Calculator for Predicting the Risk of Lower Limb Varicose Veins.

The aims of the present study were to develop and validate a predictive model for lower limb Varicose Veins, and to visualize the results using a web ...

An Explainable Artificial Intelligence Tool (FibroX) for Detecting Advanced Liver Fibrosis in Type 2 Diabetes: Protocol for a Pilot Crossover Trial.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease is highly prevalent in adults with type 2 diabetes, and advanced fibrosis is its ...

Soft multiclass feature augmented deep learning to predict tumor origins using cytology or histology whole slide images.

Tailoring cancer treatment to the primary tumor site is essential for optimal outcomes, yet identifying the source of metastasis remains a significant...

Objective quantification of chemotherapy-induced madarosis: a pilot study of an automated computer vision pipeline for eyebrow density assessment.

Chemotherapy-induced madarosis significantly impacts patient quality of life, yet current assessment methods rely heavily on subjective grading, limit...

MultiMindNet: AI-based mental health analysis using hybrid deep learning approach and Hybrid Ant-Grey Wolf Optimization (HAGWO) algorithm.

Mental health disorders like depression and anxiety pose global challenges, requiring accurate, non-invasive detection methods. Classical modes of dia...

[Expert consensus on optimizing the multidisciplinary clinical pathways and management models for pulmonary function testing].

The promotion and application of pulmonary function tests (PFTs) in China have achieved preliminary success;however, numerous deficiencies persist in ...

The multi-target cardiac protection mechanism of butylphthalide and AI-driven precision medicine: From molecular basis to clinical translation.

Butylphthalide (NBP) is a lipophilic small-molecule drug characterized by its multi-target and multi-pathway regulatory properties. Initially employed...

A multiparameter model (OsteoSC-M3) for early detection and risk stratification of osteoporosis in women: a multicentre cohort study in China.

BACKGROUND: Osteoporosis is a major global health issue, but current early screening tools lack accuracy, and the gold-standard diagnostic method, dua...

Intelligence-driven Mechanomedicine for Weight Rebound in Obesity.