Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Understanding the derivative of the cost function is key to mastering logistic regression. Learn how gradient descent updates weights efficiently in machine learning. #MachineLearning #LogisticRegress ...

ABSTRACT: Postoperative nausea and vomiting (PONV) is a common complication after anesthesia and surgery. Traditional predictive models, such as Apfel scores, rely on linear assumptions and limited ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Summer learning loss, also known as the “summer slide,” represents a significant challenge in education where students experience academic regression during extended breaks from formal instruction.

Objective: In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP ...

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 ...

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 ...

1 Department of Business Information System, Central Michigan University, Mount Pleasant, MI, USA. 2 Department of MPH, Central Michigan University, Mount Pleasant, MI, USA. 3 Department of ...