The disease is known for its strong association with climatic variables, especially excessive rainfall, high humidity, and ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

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 ...

Learn what is Logistic Regression Cost Function in Machine Learning and the interpretation behind it. Logistic Regression Cost function is "error" representation of the model.

Logistic Regression is a fundamental machine learning algorithm used for binary classification tasks. In the context of lung cancer prediction, Logistic Regression analyzes the relationship between ...

This comprehensive approach enabled the accurate identification of zero-dose children, highlighting the effectiveness of machine learning in enhancing public health initiatives and optimising ...

In the second part of the analysis, three machine learning models—Logistic Regression, Random Forest, and XGBoost—were implemented for predictive performance. Logistic Regression outperformed others ...

Machine learning has been subject to discussion from the legal and ethical points of view in recent years. Automation of the decision-making process can lead to unethical acts with legal consequences.

Machine learning models analyze complex patterns within medical datasets, enabling precise prediction and classification of diseases like CHD [14]- [18]. This study explores the application of three ...