Frontiers

Causal Machine Learning for Treatment Selection and Outcome Optimization in Mood Disorders

Mood disorders represent a major global burden and are characterized by substantial heterogeneity in symptom profiles, treatment response, and clinical ...

Apple trained an AI that captions images better than models ten times its size

Apple researchers have developed a new way to train AI models for image captioning that delivers accurate descriptions while ...

Global Artificial Intelligence (AI) In Precision Medicine Market To Attain USD 10.32 Billion By 2032, Witnessing A CAGR Of 31.35%, Says Markntel Advisors

In Precision Medicine Market To Attain USD 10.32 Billion By 2032, Witnessing A CAGR Of 31.35%, Says Markntel Advisors. NEW DELHI, March 25, 2026 /PRNewswire/ -- According to the in-depth study ...

Turning COâ‚‚ into methanol: Multilayer machine learning speeds up search for better catalysts

Finding high-performing catalysts, which are used to accelerate processes from chemical manufacturing to energy production, ...

Google Adds AI & Bot Labels To Forum, Q&A Structured Data

Google updated its Discussion Forum and Q&A Page structured data docs with new properties, including a way to label AI- and ...
Tech Xplore

Study finds AI privacy leaks hinge on a few high-impact neural network weights

Researchers have discovered that some of the elements of AI neural networks that contribute to data-privacy vulnerabilities ...
IEEE

FedMPS: Federated Learning in a Synergy of Multi-Level Prototype-Based Contrastive Learning and Soft Label Generation

Abstract: Federated learning (FL) facilitates collaborative training among multiple clients while preserving data privacy by eliminating raw data transmission. However, the inherent data heterogeneity ...
Scientific Research Publishing

H-UQ-MFF: Hybrid Uncertainty-Aware Multi-Feature Fusion for Clinically-Translatable Glaucoma Detection with FDA-Compliant Validation ()

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a ...
IEEE

iNatAg: Multi-Class Classification Models Enabled by a Large-Scale Benchmark Dataset with 4.7M Images of 2,959 Crop and Weed Species

Abstract: Accurate identification of crop and weed species is critical for precision agriculture and sustainable farming. However, it remains challenging due to visual similarity among species, ...