Biology-inspired brain model matches animal learning and reveals overlooked neuron activity

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
YouTube on MSN

Adam M Root: How to use machine learning to reduce costs and boost output

Adam M. Root argues businesses must anchor ML in customer problems, not technology. He details a strategy using ...
Analytics Insight

Best Python Tools and Frameworks for Data Science in 2026

Overview: Python supports every stage of data science from raw data to deployed systemsLibraries like NumPy and Pandas simplify data handling and analysisPython ...

Meet HealthTech AI data challenges with a single data platform

Artificial intelligence (AI) is forecast to save hundreds of thousands of lives and billions of dollars by detecting diseases ...
Scientific Research Publishing

A Brief Discussion on the Theory and Application of Artificial Intelligence in Medical Diagnostics ()

Cui, J.X., Liu, K.H. and Liang, X.J. (2026) A Brief Discussion on the Theory and Application of Artificial Intelligence in ...
Semiconductor Engineering

Benefits And Limits Of Using ML For Materials Discovery

Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development.
IEEE

AI Meets Data Science: Preprocessing and Feature Selection Reimagined

Abstract: The rapid evolution of artificial intelligence (AI) has paved the way for substantial improvements in data science workflows, particularly in data preprocessing and feature selection. These ...
IEEE

Enhancing Diabetes Diagnosis: A Comparative Study of Machine Learning Algorithms with Data Preprocessing Techniques

Abstract: The primary aim of this study is to assess the performance of various ML algorithms in diagnosing diabetes depending on various data preprocessing methods. Utilizing the Pima Indian Diabetes ...