Primary Care

Exploring exosome-related genes as candidate biomarkers in primary immune thrombocytopenia through transcriptomics and preliminary experimental validation.

Primary Immune Thrombocytopenia (ITP) is an autoimmune disease characterized by thrombocytopenia and bleeding tendency. Exosomes mediate abnormal crosstalk between immune cells and megakaryocytes in ITP, suggesting that exosome-related genes may serve as potential candidates for understanding disease pathogenesis. ITP transcriptome data and exosome-related genes (ERGs) were retrieved from public d...

A sequential deep learning model for predicting people with obesity in adults aged 18-64 using physical fitness variables.

BACKGROUND/OBJECTIVES: Health of people with obesity is a global concern. We developed an explainable sequential deep learning model using nationally representative physical fitness data to predict people with obesity and to identify the most influential predictors. SUBJECTS/METHODS: We analyzed data from 204,334 adults collected between 2010 and 2023. A sequential neural network model was trained...

Chronic phase of Chikungunya: understanding the impact of joint pain using data science and artificial intelligence.

BACKGROUND: Chikungunya is an arbovirus capable of affecting the musculoskeletal system of infected individuals. Furthermore, it has the potential to ...

Comparative diagnostic performance of machine learning models and traditional scores for HFpEF in older adults.

AIMS: Diagnosing heart failure with preserved ejection fraction (HFpEF) remains challenging, particularly in older individuals. We hypothesized that m...

Predicting Recurrence and Outcomes After Stressor-Associated Atrial Fibrillation Using ECG-Based Deep Learning.

BACKGROUND: Stressor-associated atrial fibrillation (AF) refers to new-onset AF that occurs with a reversible, acute stressor. Identifying individuals...

Predicting the Timing of the Metabolic Inflection Point in Type 1 Diabetes Progression Using Machine Learning and Survival Analysis Models.

We undertook this study to improve early identification of the metabolic inflection point (IP) preceding clinical type 1 diabetes in autoantibody-posi...

Shotgun metagenomic analysis of the oral microbiomes of children with noma.

Noma is a rapidly progressive orofacial gangrene that predominantly affects children living in extreme poverty. Despite its documentation since antiqu...

Artificial intelligence models for osteoporosis risk prediction in postmenopausal women with CKD: A cross-sectional analysis of NHANES 2005 to 2018.

Artificial intelligence (AI) can transform osteoporosis (OP) screening, but its application in high-risk, complex populations like postmenopausal wome...

Fuzzy logic for preanesthetic risk assessment in cataract surgery patients.

We aimed to build a fuzzy logic preanaesthetic risk score tailored to cataract surgery. By fusing systemic comorbidities with key patient attributes i...

Artificial Intelligence as a Catalyst for Value-Based Health Insurance in the United States: Narrative Review and Policy Perspective.

The United States health insurance system is at a critical crossroads. Inflating costs, fragmented care, and administrative inefficiencies have reveal...

Artificial intelligence in mobile health applications: A comprehensive review of its role in diabetes care.

This review explores the integration of artificial intelligence (AI) in mobile health applications for diabetes care. It focuses on key AI methodologi...

Multi-representation machine learning approaches for screening aurora kinases A & B inhibitors and insights from structural alerts.

The Aurora kinase (AURK) family enzymes are almost identical to the serine or threonine kinase (STK), and they are essential for various cell function...

Artificial intelligence in medicine: a scoping review of the risk of deskilling and loss of expertise among physicians.

BACKGROUND: Artificial intelligence (AI) systems are increasingly deployed in clinical practice, particularly in radiology, pathology, endoscopy, and ...

Challenges and Opportunities for Improved Tuberculosis and HIV Prevention in South America.

Tuberculosis (TB) and human immunodeficiency virus (HIV) cause significant morbidity and mortality in South America. Despite the advances in active ca...

AI-based triage and decision support in mammography and digital tomosynthesis for breast cancer screening: a paired, noninferiority trial.

Artificial intelligence (AI) systems have been demonstrated to improve the accuracy of screening mammograms. Here this prospective, paired, noninferio...

Behavioural, cognitive, and computational risk factors for type 2 diabetes: A systematic review.

BACKGROUND: Type 2 diabetes mellitus represents a global public health challenge, with rising prevalence driven by complex interactions between lifest...

Artificial Intelligence in Type 1 Diabetes Management: A Scoping Review of Randomised Controlled Trials.

BACKGROUND: Artificial intelligence is emerging in healthcare systems. In type 1 diabetes, AI-enabled tools are increasingly used to support nutrition...

Graph-Enhanced Multi-Task Learning for Type 2 Diabetes Comorbidity Risk Prediction.

Early prediction of Type 2 diabetes mellitus (T2DM) complications holds significant clinical importance for improving patient outcomes and reducing he...

Machine Learning-Based Risk Prediction for Coronary Heart Disease Complicated by Hyperhomocysteinemia: Retrospective Study.

BACKGROUND: Hyperhomocysteinemia (HHcy) is recognized as an independent risk factor for coronary heart disease (CHD), yet accurately predicting CHD ri...

Personalized Glucose Management With AI: Pilot Study Using a Multiarmed Bandit Approach.

BACKGROUND: Personalized behavioral recommendations through mobile apps have proven effective in preventing serious chronic diseases such as diabetes....