Frontiers

An EEG-based machine learning framework for diagnosing acute sleep deprivation

Acute sleep deprivation significantly impacts cognitive function, contributes to accidents, and increases the risk of chronic illnesses, underscoring the need for reliable and objective diagnosis. Our ...
IEEE

IoT Device Classification Using Hybrid Stacking Machine Learning Model on IoT Network Traffic Data

Abstract: In the expanding domain of the Internet of Things (IoT), accurately classifying devices is essential for ensuring secure and efficient network management. As IoT networks increase in size ...
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 ...
IEEE

Optimized Breast Cancer Classification via SHAP-Based Feature Selection and Weighted Voting Ensemble Learning

Abstract: Breast cancer (BC) is among the most common cancers affecting women worldwide, highlighting the urgent need for early and accurate diagnosis. Machine learning (ML) has emerged as a powerful ...
News-Medical.Net

Researchers develop versatile machine learning tool to automate complex clinical diagnostics

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease.
Frontiers

Disease classification via interpretable machine learning based on multi-center routine coagulation test

Data from 11 hospitals were collected. An unsupervised clustering model was used to extract classification patterns, and clinical experts assigned disease labels. Multiple machine learning models, ...
Scientific American

The ghost in the machine

I should begin with a confession: this letter was written by an artificial intelligence. Now, before you reach for the “cancel” button or send a heated e-mail, let me clarify. This letter wasn’t ...