Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

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

Enhanced risk prediction of femoral head osteonecrosis in the elderly: a comparative study of random forest and logistic regression models

Department of Orthopedics, Shanxi Bethune Hospital, Tongji Shanxi Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Taiyuan, China Background and aim: ...
Scientific Research Publishing

Saito, T. and Rehmsmeier, M. (2015) The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets.

ABSTRACT: Accurately predicting individual responses to antidepressant treatment is a critical step toward achieving personalized psychiatry and minimizing the ...
The New York Times

A La Liga match in… Miami? Plus: Liverpool need fine-tuning, Musah’s Nottingham Forest talks

The Athletic FC ⚽ is The Athletic’s daily football (or soccer, if you prefer) newsletter. Sign up to receive it directly to your inbox. Hello! Christmas in Miami for La Liga? You heard it here first.
Frontiers

Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics

Background: Inflammatory bowel disease (IBD) poses significant mortality risks for critically ill patients requiring intensive care unit (ICU) admission, driven by complications such as malnutrition, ...
GitHub

Pull requests: Nisa1863/Diabetes-Classification-with-Random-Forest-Decision-Tree-KNN-and-Hyperparameter-Tuning

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.
Scientific Research Publishing

Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1, Article 9.

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
IEEE

Implementation of Random Forest Model with Hyperparameter Tuning for Diabetes Mellitus Classification

Abstract: This research aims to classify Diabetes Mellitus (DM) using the Random Forest (RF) model by exploring feature selection techniques and hyperparameter tuning. DM is a metabolic disorder in ...