Objectives Metabolic-associated fatty liver disease (MAFLD) is becoming increasingly prevalent worldwide, however, early ...
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 ...
Background: Enteral Nutrition-Associated Diarrhea (ENAD) is a common complication in critically ill patients, significantly impacting clinical outcomes. Accurately predicting the risk of ENAD is ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
3 Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 4 Yong Loo Lin School of Medicine, National University of Singapore, Singapore 5 ...
1 Information System Department, Faculty of Commerce and Business Administration Helwan University, Cairo, Egypt. 2 Computer Science Department, Faculty of Computer and Artificial Intelligence, Helwan ...
In this project, we leverage the power of artificial intelligence in healthcare to predict lung cancer risks. By employing various machine learning techniques, we aim to assist medical professionals ...
The primary goal of this project is to leverage machine learning algorithms to predict the likelihood of an individual developing lung cancer. By examining key patient data points and employing data ...
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