Mar 29, 2017 · Healthcare Prediction Analysis in Big Data using Random Forest Classifier. Authors: Subhapriya. P, R. Sujatha, K. Meghana. View PDF Save PDF.

Submission Deadlines, Ongoing Submissions ; Online Publishing, Immediate (after review) ; Author Notification, 2 days of submission ; Final Issue, 30th June, 2024.

Jun 30, 2024 · Article. Full-text available. Using network data envelopment analysis to assess the sustainability and resilience of healthcare su... October ...

ABSTRACT. The Healthcare exchange generally clinical diagnosis is ended commonly by doctor's knowledge and practice. Computer Aided Decision Support System.

The random forest algorithm is as follows: k indicates the number of decision tree in the random forest, n suggests the number of training data-set sample ...

In this work, we used six algorithms Logistic Regression, K Nearest Neighbors, Decision Tree, Support Vector Machine, Naïve Bayes, and Random Forest. The ...

An Enhanced Random Forest Classifier to detect Crop Disease with Texture and Shape Features OF Corn Images (ERFCTS)Year : 2024. Name of the Journal ...

Jan 15, 2024 · This paper aims to provide a comprehensive overview of the current research on the application of face recognition technol- ogy to disease ...

Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which ...

Random Forest. Random Forest is a widely used machine learning method. It is a method used to address classification and regression issues. The "forest" is a ...