Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
It’s been discovered that a new tool using routine blood tests and a simple online app could help detect tuberculosis (TB) ...
“There are known knowns. There are known unknowns. But there are also unknown unknowns—things we do not yet realize we do not know.”—Donald Rumsfeld (2002) While modern machine learning (ML) ...
Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...
ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...
1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
1 Department of Science and Education, Shenyang Maternity and Child Health Hospital, Shenyang, China 2 Department of Maternal, Child and Adolescent Health, School of Public Health, Shenyang Medical ...
Google has added a 'Guided Learning' mode in Gemini to promote deeper understanding of complex topics and concepts. It's available for free to all Gemini users. You can upload your course materials, ...
Objective: This study aims to develop and validate a machine learning model that integrates dietary antioxidants to predict cardiovascular disease (CVD) risk in diabetic patients. By analyzing the ...
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