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 ...

ML powered system that predicts most suitable crop using ensemble(hard voting) of Decision Tree, Random Forest, and Gradient Boosting models implemented from scratch ...

Background: Heart failure (HF), with its distinct phenotypes, poses significant public health challenges. Early diagnosis of specific HF phenotypes is crucial for timely therapeutic intervention.

The U.S. Forest Service has announced it is reversing a ban on federal firefighters wearing masks, and will give crews protective N95s as they battle increasingly intense fires across the nation. For ...

The goal of this project is indentify fraudulent transactions while minimizing false positives (non-fraudulent transactions flagged as fraud) and false negatives (missed fraudulent transations). The ...

Background: Decisions surrounding involuntary psychiatric treatment orders often involve complex clinical, legal, and ethical considerations, especially when patients lack decisional capacity and ...

Abstract: The study aims to improve the accuracy of cyberbullying detection. Compared to the Random Forest classifier, utilize XGBoost to improve accuracy. In this study, two groups were compared. The ...

A novel framework integrates urban surveillance video data with a two-stage AI pipeline: an enhanced random forest classifier detects rain streaks and selects key image regions, while a hybrid deep ...

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 ...

ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...