Primary Care

Developing an ICU Mortality Risk Prediction Model for Acute Myocardial Infarction Patients Based on Machine Learning

Patients with acute myocardial infarction (AMI) are in a critical condition, facing a high risk of death in the intensive care unit (ICU) with significant individual differences. The aim of this study is to integrate clinical data using machine learning algorithms to construct a model for predicting the risk of death in ICU for AMI patients, thereby providing clinicians with an objective risk asse...

Real-world deployment of remote sleep monitoring technologies reveals distinct patterns associated with cognitive decline

Sleep disturbances and altered circadian rhythms are well-documented in both physiological and biological studies of dementia. The exact causal relationship remains unclear. Several other long-term health conditions may also influence sleep patterns. Examining sleep patterns in relation to chronological ageing and the variations and progression of dementia, considering factors such as age, sex, an...

Risk prediction for lung cancer screening: a systematic review and meta-regression

Lung cancer (LC) is the leading cause of cancer mortality, often diagnosed at advanced stages. Screening reduces mortality in high-risk individuals, b...

Enhanced Diabetes Prediction Using Novel Additive-Multiplicative Neural Networks: A Comprehensive Machine Learning Analysis of the PIMA Indians Dataset

Early diabetes detection remains challenging, requiring robust machine learning approaches that balance accuracy with clinical interpretability for ef...

RT2C: Predicting Time to New Dental Caries Using a Recurrent Neural Network Model Trained on Multi-Site Longitudinal Structured Dental Data

Dental caries remains one of the most prevalent chronic conditions globally, yet efforts to quantify a patient’s risk of developing new caries over ti...

Deep learning-based prediction of cardiopulmonary disease in retinal images of premature infants

Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are leading causes of morbidity and mortality in premature infants. To determine whet...

Identifying High-Risk Adolescents for Mental Health Difficulties: A Machine Learning Analysis of the Health Behaviour in School-aged Children Study Across 46 Countries

Adolescent mental health represents a global public health crisis, yet traditional surveillance methods lack the scalability and predictive power need...

MedRAGent: An Automatic Literature Retrieval and Screening System Utilizing Large Language Models with Retrieval-Augmented Generation

Systematic reviews play a critical role in synthesizing evidence across numerous studies, providing a foundation for informed decision-making in medic...

Compartment-specific Fat Distribution Profiles have Distinct Relationships with Cardiovascular Ageing and Future Cardiovascular Events

Obesity is a global public health priority and a major risk factor for cardiovascular disease (CVD). Emerging evidence indicates variation in patholog...

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging

Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid...

ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care

Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse be...

Development of a Hypertension Risk Prediction Model using Nationally Representative Survey Data: A Machine Learning Approach and Web Application Deployment

Hypertension is a major modifiable risk factor for cardiovascular diseases. Early identification of high-risk individuals using predictive models can ...

Plasma Proteomics Linking Primary and Secondary diseases: Insights into Molecular Mediation from UK Biobank Data

Diabetes, hypertension, and dyslipidemia are major risk factors for cardiovascular (CVD), cerebral, and renal diseases (RD). However, the underlying m...

Plasma proteome profiling identifies predictive signatures for preterm birth risk

Preterm birth (PTB) is a major public health concern, and its associated complications account for 16.6% of deaths in children under five years. Over ...

Early Prediction of Gestational Diabetes Using Integrated Cell-free DNA Features and Omics-derived Genetic Scores

Gestational diabetes mellitus (GDM) affects 15.6% of pregnancies globally, with Vietnam exhibiting one of the highest prevalences at 21%. Current diag...

Machine Learning Prediction of Pharmacogenetic Test Uptake Among Opioid-Prescribed Patients Using Electronic Health Records: A Retrospective Cohort Study

Opioids are a widely prescribed class of medication for pain management. However, they have variable efficacy and adverse effects among patients, due ...

Comprehensive, Transparent, and Fair Machine Learning Models for Hypertension Risk Prediction: Benchmarking With Framingham, External Validation, Individual-Level Analysis, and Equitable Clinical Utility

Hypertension (HTN) is a leading, yet often underdiagnosed, cause of cardiovascular diseases worldwide. While clinical risk scores like the Framingham ...

Clustered Phenotypes of Hypertensive Heart Disease With Strain Measurements Reveals Distinct Characteristics, Clinical Course, and Prognosis

Hypertensive heart disease (HHD) encompasses diverse clinical profiles, comorbidities, and cardiac remodeling, but current classifications insufficien...

Internal and External Validation of Machine Learning Algorithms Versus FINDRISC for Incident Type 2 Diabetes: A Transparent, Explainable Benchmark Using SHAP

Type 2 diabetes mellitus (T2DM) affects almost half a billion people, and the projected cost is $2.25 trillion by 2030; early detection strategies are...

A Self-Explainable Dynamic Risk Monitoring Framework for Predicting Alzheimer’s Disease and Related Dementias

Alzheimer’s Disease and Related Dementias (ADRD) affect millions worldwide and can begin over a decade before symptoms appear. ADRD are generally irre...