Primary Care

An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk Estimation

Reliable prediction of pediatric obesity can offer a valuable resource to providers, helping them engage in timely preventive interventions before the disease is established. Many efforts have been made to develop ML-based predictive models of obesity, and some studies have reported high predictive performances. However, no commonly used clinical decision support tool based on existing ML models...

Predicting Emergency Department Visits for Patients with Type II Diabetes

Over 30 million Americans are affected by Type II diabetes (T2D), a treatable condition with significant health risks. This study aims to develop and validate predictive models using machine learning (ML) techniques to estimate emergency department (ED) visits among patients with T2D. Data for these patients was obtained from the HealthShare Exchange (HSX), focusing on demographic details, diagn...

Access to care improves EHR reliability and clinical risk prediction model performance

Disparities in access to healthcare have been well-documented in the United States, but their effects on electronic health record (EHR) data reliabi...

Machine Learning Algorithms for Detecting Mental Stress in College Students

In today's world, stress is a big problem that affects people's health and happiness. More and more people are feeling stressed out, which can lead ...

Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.

This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on the development of cardiovascular diseases (CVD) ...

Electronic Health Records-Based Data-Driven Diabetes Knowledge Unveiling and Risk Prognosis

In the healthcare sector, the application of deep learning technologies has revolutionized data analysis and disease forecasting. This is particular...

High-Throughput Detection of Risk Factors to Sudden Cardiac Arrest in Youth Athletes: A Smartwatch-Based Screening Platform

Sudden Cardiac Arrest (SCA) is the leading cause of death among athletes of all age levels worldwide. Current prescreening methods for cardiac risk ...

Take Your Steps: Hierarchically Efficient Pulmonary Disease Screening via CT Volume Compression

Deep learning models are widely used to process Computed Tomography (CT) data in the automated screening of pulmonary diseases, significantly reduci...

Exploring Long-Term Prediction of Type 2 Diabetes Microvascular Complications

Electronic healthcare records (EHR) contain a huge wealth of data that can support the prediction of clinical outcomes. EHR data is often stored and...

Predicting Suicides Among US Army Soldiers After Leaving Active Service.

IMPORTANCE: The suicide rate of military servicemembers increases sharply after returning to civilian life. Identifying high-risk servicemembers befor...

Artificial intelligence-aided data mining of medical records for cancer detection and screening.

The application of artificial intelligence methods to electronic patient records paves the way for large-scale analysis of multimodal data. Such popul...

A Voice-based Triage for Type 2 Diabetes using a Conversational Virtual Assistant in the Home Environment

Incorporating cloud technology with Internet of Medical Things for ubiquitous healthcare has seen many successful applications in the last decade wi...

Graph-Based Biomarker Discovery and Interpretation for Alzheimer's Disease

Early diagnosis and discovery of therapeutic drug targets are crucial objectives for the effective management of Alzheimer's Disease (AD). Current a...

Scaling Structure Aware Virtual Screening to Billions of Molecules with SPRINT

Virtual screening of small molecules against protein targets can accelerate drug discovery and development by predicting drug-target interactions (D...

Machine learning-enabled virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations.

Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat ...

Primary care research on hypertension: A bibliometric analysis using machine-learning.

Hypertension is one of the most important chronic diseases worldwide. Hypertension is a critical condition encountered frequently in daily life, formi...

Leveraging Gene Expression Data and Explainable Machine Learning for Enhanced Early Detection of Type 2 Diabetes

Diabetes, particularly Type 2 diabetes (T2D), poses a substantial global health burden, compounded by its associated complications such as cardiovas...

Artificial Intelligence Chatbots in Patient Communication: Current Possibilities.

ChatGPT, an artificial intelligence (AI) chatbot, can generate text prompts based on user input. This study investigated the possibility of utilizing ...

[Research progress in the application of virtual artificial intelligence in risk assessment and diagnosis of periodontal disease].

Periodontal disease is a common and frequently-occurring disease in China. Early detection, diagnosis, and treatment of periodontal disease are of gre...

Equivariant Graph Attention Networks with Structural Motifs for Predicting Cell Line-Specific Synergistic Drug Combinations

Cancer is the second leading cause of death, with chemotherapy as one of the primary forms of treatment. As a result, researchers are turning to dru...