A Systematic Review of Adoption, Barriers and Strategic Implications and published in Administrative Sciences, reviewed 37 peer-reviewed studies from 2015 to 2025 and found that AI-driven demand ...

To develop a non-invasive diagnostic method for pelvic chondrosarcoma using clinical and radiological features, aiming to improve early diagnostic accuracy and reduce reliance on invasive biopsies.

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

A Python implementation of the Truly Spatial Random Forests (SRF) algorithm for geoscience data analysis. Based on: Talebi, H., Peeters, L.J.M., Otto, A. & Tolosana ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...

Cholelithiasis, commonly known as Gallstone disease, occurs when hardened deposits form in the gallbladder or bile ducts. It affects millions of people worldwide and is especially common in women.

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...

Abstract: Random Forest is an efficient machine learning classification algorithm known for its high accuracy and interpretability. However, the traditional voting mechanism in the standard Random ...

Abstract: The purpose of this study is to predict obesity using KNN algorithm compared with Random Forest algorithm. This research paper focuses on the creation of a novel method for obesity ...