Feasibility and Implementation of a Digital Health Intervention Electronic Patient-Reported Outcomes–Based Platform for Telemonitoring Patients With Breast Cancer Undergoing Chemotherapy Among the 76 ...

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Heart failure is a leading cause of hospitalization and long-term disability, with many individuals progressing from subclinical disease to overt symptoms ...

Understanding and preventing drug side effects holds a profound influence on drug development and utilization, profoundly impacting patients’ physical and mental well-being. Traditional artificial ...

Researchers captured volunteers′ facial image data using a 3D face instrument and collected their medical metadata from their physical examinations, extensive questionnaires, and so on. Through the ...

Performance evaluation of an AI-powered system for clinical trial eligibility using mCODE data standards. ATheNa-Breast: A real-world pilot of an artificial intelligence (AI) chatbot using therapy ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...