Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
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 ...
Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to “here’s what to do.” ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
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, ...
Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...
When everyone has access to the same AI models, the same AI-enabled tools, and the same vendor ecosystem, organizational context becomes the differentiator. Context is demonstrated execution: the ...
BACKGROUND: BCR-ABL tyrosine kinase inhibitors (TKIs) have been increasingly linked to pulmonary arterial hypertension (PAH) since 2009, although supporting evidence is limited. Our objective was to ...