What makes a genus real? Scientists use tree bats to evaluate a testable '2 Sigma Genus Concept'

Dr. Amy Baird, Professor of Biology at the University of Houston-Downtown (UHD), and her colleagues are seeking to change the attitude of biologists toward the meaning of taxonomic categories above ...

AI model predicts chemical effects on gene expression, speeding drug discovery

Inside a diseased cell, the genes are in chaos. Some are receiving signals to overproduce a protein. Others are reducing ...
MIT Technology Review

The Pentagon is planning for AI companies to train on classified data, defense official says

The generative AI models used in classified environments can answer questions but don't currently learn from the data they ...
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 ...
Scientific Research Publishing

A Wind Speed Prediction Model Based on Machine Learning in Guyuan Area ()

1 School of Atmospheric Sciences, Chengdu University of Information and Technology, Chengdu, China. 2 Guyuan Meteorological Bureau, Guyuan, China. 3 Jilin Provincial Institute of Meteorological ...
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

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
Frontiers

Explainable machine learning model for predicting the outcome of acute ischemic stroke after intravenous thrombolysis

Acute ischemic stroke (AIS) patients often experience poor functional outcomes post-intravenous thrombolysis (IVT). Novel computational methods leveraging machine learning (ML) architectures ...