Science Daily

AI may not need massive training data after all

New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers ...
Tech Xplore

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
SDxCentral

AI inferencing will define 2026, and the market's wide open

AWS, Cisco, CoreWeave, Nutanix and more make the inference case as hyperscalers, neoclouds, open clouds, and storage go ...

A zero-shot learning framework for maize cob phenotyping

A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...
eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
Open Heart

Development and validation of a deep learning model for severe mitral stenosis detection from chest X-rays

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
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 ...
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) ...

LNS Research Names Seeq Front Runner in Industrial AI: Advanced Analytics Solution Selection Matrix

Seeq, the global leader in industrial analytics, AI, and enterprise monitoring for industrial companies, today announced that it has been named a Front Runner within the inaugural Industrial AI: ...
IEEE

Patch-Based Deep-Learning Model With Limited Training Dataset for Liver Tumor Segmentation in Contrast-Enhanced Hepatic Computed Tomography

Abstract: The automatic segmentation of liver tumors plays an important role in the diagnosis and treatment of liver cancer. While deep convolutional neural network (DCNN) models are widely used for ...