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 ...

Mr. Currell was a deputy undersecretary and senior adviser at the Department of Education from 2018 to 2021. He is a trustee of Gustavus Adolphus College in St. Peter, Minn. This week, about 200,000 ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

If you’ve ever tried to build a agentic RAG system that actually works well, you know the pain. You feed it some documents, cross your fingers, and hope it doesn’t hallucinate when someone asks it a ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...

Abstract: This study utilizes decision tree and logistic regression models to explore the factors contributing to medical claim denials and identify areas for improvement. We adapt undersampling ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...

Balancing water quality standards while facilitating economic growth with uncertain factors in a complex system is challenging for policy makers. This case study analyses the fictional town of Fortuna ...

Decision trees are a powerful tool for decision-making and predictive analysis. They help organizations process large amounts of data and break down complex problems into clear, logical steps. Used in ...

1 Department of Nursing, Harbin Medical University, Harbin, China 2 Department of Nursing, Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun, China Objective: This ...