Objective The aim of this systematic literature review was to provide a comprehensive and exhaustive overview of the use of machine learning ... prediction metrics such as accuracy, sensitivity, ...

SEVEN engineers behind the rise of the artificial intelligence technologies that are revolutionising industries and ...

While ML models are powerful tools for predicting diabetes, their lack of interpretability presents a major challenge for clinical adoption. Healthcare professionals require AI models to not only be ...

Antimicrobial resistance is a growing health crisis that could lead to millions of deaths by 2050, according to the World ...

Advancements in machine learning are reshaping protein structure prediction, offering efficient tools that enhance drug ...

CA is commonly used in disease prediction models ... (SENet), and multitask learning was developed to estimate ECG-BA from 12-lead ECGs. The model was optimized using the Adam optimizer, which ...

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Heart disease remains the leading cause of death in the U.S., with nearly 2,500 deaths daily due to cardiovascular issues. The prevalence of risk factors like hypertension, obesity, and type 2 ...