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 for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer ...
11don MSN
Machine learning model predicts serious transplant complications months before symptoms appear
A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...
Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
A machine learning model predicted cardiac tamponade during AF ablation with high accuracy. Learn how XGBoost may improve ...
BIOPREVENT’ AI tool predicts transplant-related immune conflict and mortality risk using biomarkers, helping doctors ...
A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...
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