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.
Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...
An intelligent spam detection system that classifies SMS/email messages with 98.48% accuracy using machine learning. This project compares multiple algorithms and provides comprehensive performance ...
Abstract: Given the fact that smart grids integrate distributed energy resources and advance communication technologies, which have high security vulnerability to the attack of denying service (DoS), ...
To construct a diagnostic model of osteoarthritis related to methylation genes using machine learning algorithms, and analyze its prognostic value and biological functions. The GSE 63695 and GSE162484 ...
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