Preventive Care

Advances in Newborn Screening for Sickle Cell Disease: A Systematic Review of Diagnostic Methods and Innovations

Sickle cell disease (SCD) is one of the most prevalent hemoglobinopathies worldwide, particularly in regions with high genetic predisposition. Early diagnosis through newborn screening (NBS) is critical for initiating interventions that significantly reduce morbidity and mortality. This systematic review evaluates the current methodologies used in NBS for SCD, comparing their sensitivity, specific...

Hypertension Screening via Awake-Sleep Differences in Photoplethysmogram Signals

Hypertension is a major risk factor for cardiovascular diseases. This study proposes a novel hypertension screening framework based on awake-sleep differences in photoplethysmography (PPG) indices, using machine learning. We hypothesised that normotensive individuals exhibit greater PPG variation between awake and sleep states than unmanaged hypertensive individuals. The Aurora-BP dataset (n=180; ...

Datasheet for the IDHea Primary Eye Care Dataset: A Real-World Ocular Imaging Resource for Research

Real-world ocular imaging datasets are essential for advancing research in artificial intelligence (AI), autonomous disease screening, and clinical de...

AI Implementation in U.S. Healthcare and Its Association With Elder Mortality and Quality of Care

Hospitals are increasingly adopting artificial intelligence (AI) tools in clinical care. However, their overall impact on the health of older adults r...

SmokeBERT: A BERT-based Model for Quantitative Smoking History Extraction from Clinical Narratives to Improve Lung Cancer Screening

Tobacco use is a critical risk factor for diseases such as cancer and cardiovascular disorders. While electronic health records can capture categorica...

Clinical Validation and Machine Learning Optimization of MyCog: A Self-Administered Cognitive Screener for Primary Care Settings

Primary care presents an ideal opportunity for early detection of cognitive impairment, yet primary care clinics face barriers to cognitive screening....

Mapping Inequities in Global Vaccine Sentiment Research

Negative public sentiment towards vaccination (PSV) poses significant challenges to the effectiveness of immunization programs, with dramatic effects ...

Artificial Intelligence for Pre-Anaemic Iron Deficiency Detection Using Rich Complete Blood Count Data

Iron deficiency (ID) is a major contributor to global disease burden and the leading cause of anaemia. Early detection is important for proactive mana...

Diagnostic accuracy of a high-throughput multiplex immunoassay for the detection of Mpox virus infection and MVA-BN vaccination up to two years after exposure

Mpox, caused by mpox virus (MPXV), has gained global attention following the 2022 Clade IIb outbreak and the emergence of two novel Clade I lineages i...

Artificial Intelligence-Driven Innovations in Diabetes Care and Monitoring

This study explores Artificial Intelligence (AI)’s transformative role in diabetes care and monitoring, focusing on innovations that optimize patient ...

Integrating GWAS and Transcriptomic Data Using PrediXcan and Multimodal Deep Learning Reveals Genetic Basis and Drug Repositioning Opportunities for Alzheimer’s Disease

Alzheimer’s disease (AD), the leading cause of dementia, imposes a significant societal and economic burden; however, its complex molecular mechanisms...

M-PreSS: A Model Pre-training Approach for Study Screening in Systematic Reviews

Conducting a systematic review is labour-intensive and time-consuming, especially during the study screening process. Previous research has introduced...

Evaluation of the Bangkok Health Research and Ethics Interest Group: reflecting on the experiences of group members, researchers and facilitators participating in an urban community advisory board in Thailand

The Mahidol Oxford Tropical Medicine Research Unit (MORU), headquartered in Bangkok, conducts research on tropical medicine and global health. MORU wo...

Data-driven discovery of core sleep biomarkers for predicting early cardiometabolic risk in a healthy population using machine learning

Identifying robust biomarkers for future cardiometabolic risk within the crucial “ preventive window” in healthy individuals remains a major challenge...

Modeling the Impact of Social Determinants on Breast Cancer Screening: A Data-Driven Approach

This study addresses the critical implementation science challenge of operationalizing social determinants of health (SDoH) in clinical practice. We d...

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

Identifying reasons for missed preventive care, such as follow-up colonoscopy after an abnormal stool-based colon cancer screening test, is critical f...

Application of Machine Learning Approaches to Develop Predictive Models for Diabetes and Hypertension among Bangladesh Adults

With rapid urbanization, lifestyle changes, and an aging population, non-communicable diseases (NCDs), including hypertension and diabetes, pose signi...

Design and Implementation of an End-to-End AI-Driven Colonoscopy Recall Workflow at Scale

We present a real-world deployment of a large language model-powered colonoscopy recall pipeline that structured over 100,000 patient records during a...

Artificial Intelligence in Gastrointestinal Endoscopy: A Comprehensive Systematic Review

Artificial intelligence (AI) has emerged as a transformative force in gastrointestinal (GI) endoscopy, offering enhancements in diagnostic accuracy, l...

A 60-Second Interpretable Voice Model for Early Dementia Screening

Early detection of cognitive impairment in assisted living is hindered by time-intensive tools like MMSE and MoCA. We present a 60-second voice-based ...