A machine learning model that uses DNA methylation patterns may help identify the origin of cancers of unknown primary

A machine learning model analyzing CpG-based DNA methylation accurately predicted the origin of many different cancer types ...
Tech Xplore

This AI mines the numbers buried in scientific papers and turns them into usable data fast

Numbers are the language of science—yet in research articles, they are often buried within the text and difficult to analyze.

Tracing anglers in the Gulf Coast: New machine learning tools reveal when, where and how anglers fish

The Gulf Coast is recognized worldwide for its exceptional fishing opportunities, offering anglers a wide variety of species ...
IEEE

Binary malware image classification using machine learning with local binary pattern

Abstract: Malware classification is a critical part in the cyber-security. Traditional methodologies for the malware classification typically use static analysis and dynamic analysis to identify ...
Frontiers

Chlamy_ChloroPred: a deep learning-based, highly accurate binary classifier for chloroplast protein prediction in the model microalga, Chlamydomonas reinhardtii, with potential ...

The chloroplast, a living relic of an ancient endosymbiotic interaction between a microalga and a microbe and the principal subcellular organelle responsible for biological CO 2 assimilation, is ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
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

Neutral Class Handling for Customer Sentiment Analysis In Binary Classification: A Comparative Study of Supervised Machine Learning Classification Algorithm

Abstract: Customer sentiment analyses improve customer experience and ultimately drive business success. Polarity classification is considered the standard research task in sentiment analysis. This ...