Devdiscourse

Food industry turns to machine learning to boost efficiency, cut waste and improve quality

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
Devdiscourse

AI takes the helm in power systems facing renewable and carbon pressures

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
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 ...
NERDBOT

How AI Data Matching Works: From Search Query to Perfect Dataset

Introduction Artificial Intelligence lives on data. Without data, large language models (LLMs) cannot learn, adapt, or make ...
Technology Networks

Single-Cell Technologies Are Redefining Our Understanding of Human Development

This article explores how single-cell multiomics and spatial transcriptomics are illuminating early pregnancy, uncovering ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Science Daily

AI learns to decode the diseases written in your DNA

A newly developed AI can predict which diseases specific genetic mutations are likely to cause, not just whether they are harmful. The breakthrough could speed up diagnoses and open new paths for ...
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) ...