Scientific Research Publishing

Proposal for a Machine Learning Model to Improve Hauling Productivity in an Open-Pit Mine ()

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...
PC Tech Magazine

Inside the AI Systems That Catch Fake Clicks in Real Time

Ad fraud is no longer a fringe issue. It is a systemic threat to digital advertising, and its scale demands a technological ...
Scientific Research Publishing

Hybrid Deep Learning Model for Breast Cancer Classification in Low-Middle Income Countries: A MobileNetV2 and Cubic SVM ()

Breast cancer is one of the major causes of female death in any part of the world, and the burden is highly ...
Scientific American

AI techniques speed up forensic analysis of crucial crime scene larvae

To use this evidence, investigators typically must grow the larvae until adulthood in a laboratory setting and then identify ...
The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
IEEE

A Comprehensive Analysis of Classic Machine Learning and Deep Learning Modeling for Breed Recognition of Bananas

Abstract: Bananas are among the world’s most widely farmed, traded, and consumed fruits. Bananas contain several vitamins and minerals, including vitamin B6, vitamin C, magnesium, and manganese.
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
IEEE

Distributed Multi-Task In-Network Classification on Programmable Switches by Ensemble Models

Abstract: Offloading machine learning models for network classification on high-throughput programmable switches is a promising technology, enabling line-speed in-network classification. Existing ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.