Who is a data scientist? What does he do? What steps are involved in executing an end-to-end data science project? What roles ...

The job market faces a persistent gap between AI knowledge and practical application. Employers seek professionals who can navigate real-world challenges.

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Abstract: In today’s digital era, where information flows seamlessly and is readily available and accessible. However, these information and communication systems are highly dependent on the ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

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 ...

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 ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Background: Acute ST-segment elevation myocardial infarction (STEMI) is a cardiovascular emergency that is associated with a high risk of death. In this study, we developed explainable machine ...

This video is a one stop shop for understanding What is linear regression in machine learning. Linear regression in machine learning is considered as the basis or foundation in machine learning. This ...