Understanding the derivative of the cost function is key to mastering logistic regression. Learn how gradient descent updates ...

According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...

By Priyanjana Pramanik, MSc. By combining oxidative stress biology with advanced machine learning, researchers show how a ...

Predictive Analytics is a sophisticated forecasting system that relies on data mining, statistical modelling, and machine learning. It is an offshoot of advanced analytics that uses historical data to ...

The researchers argue that their findings, published in Scientific Reports, could help clinicians anticipate which patients ...

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 ...

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 ...

Abstract: For the past decade, cardiac infection is the important source of death for several populations around world. Nowadays, heart attacks occurring in the younger generation are becoming common.

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 ...