Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
AI & Society, states that algorithmic systems often construct competing but equally valid “model-worlds,” offering empirical support for a philosophical claim that evidence alone cannot uniquely ...
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 for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
Read more about AI-driven learning analytics struggle to deliver measurable gains in higher education on Devdiscourse ...
New research shows supervised machine learning models combining Helicobacter pylori genomic data with patient demographics can accurately predict gastric cancer risk.
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
EXtreme Gradient Boosting (XGBoost), a machine learning model, outperformed more traditional methods for predicting composite major adverse events (MAEs) and many individual events in patients ...
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