A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

Retail LLMs promise raw computing power in edge settings. But what are the considerations that face decision-makers in the sector?

Machine learning has seemingly slipped from its rightfully-earned pedestal. Its current state is an almost baffling one. Over ...

Intelligent Document Processing (IDP) is now making this a reality, transforming unstructured chaos into a structured goldmine of valuable information. However these are a musts; Capture isn’t just ...

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a significant obstacle in transferring research datasets to actual clinical settings.

Abstract: This study investigates the effectiveness of combining deep learning-based feature extraction with classical machine learning classifiers for the task of litter image classification, aiming ...

Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, ...

Can Canada own the AI industry it helped invent? A new report explores AI sovereignty and the roadmap to changing our ...

Drug-drug interactions (DDI) can cause adverse drug reactions during the co-administration of multiple drugs, necessitating accurate and scalable prediction tools. While deep learning models have ...

The historic first image of the Messier 87 (M87) supermassive black hole, captured using the Event Horizon Telescope, has been sharped using a machine learning technique called PRIMO. PRIMO is short ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...