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.
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 ...
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 ...
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Using AI to predict earthquakes: Machine learning detects subtle changes before lab-scale fault failures
Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been thought to forebode earthquakes are not supported by empirical evidence. As ...
Heart failure is a leading cause of hospitalization and long-term disability, with many individuals progressing from subclinical disease to overt symptoms ...
Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...
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 ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
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