Objective: To evaluate the utility and effectiveness of the recombinant Mycobacterium tuberculosis fusion protein (EC) skin test for tuberculosis (TB) screening among student populations in ...

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 ...

Researchers have developed a new computer-aided diagnosis (CAD) system, BREAST-CAD, to improve breast cancer detection accuracy using machine learning algorithms and a real-time client-server ...

Abstract: Decision tree is a machine learning algorithm that can effectively predict student performance. However, the existing performance prediction models rarely analyze the impact of multiple ...

Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify tomatoes ...

Abstract: This paper presents an automatic machine learning (autoML) algorithm to select a decision tree algorithm which is most suitable for the stated requirements by the user for classification.

This project uses Weka to analyze the "Car Evaluation" dataset with decision trees, comparing model performance on 70/30 and 50/50 data splits. It includes accuracy, F1-scores, and decision tree ...

ABSTRACT: Decision tree is an effective supervised learning method for solving classification and regression problems. This article combines the Pearson correlation coefficient with the CART decision ...

ABSTRACT: Decision tree is an effective supervised learning method for solving classification and regression problems. This article combines the Pearson correlation coefficient with the CART decision ...

Discordance Between the Initial Diagnosis of Sarcomas and Subsequent Histopathological Revision and Molecular Analyses in a Sarcoma Reference Center in Brazil In this prospective study of 170 patients ...