Federal Register

Medical Devices; Radiology Devices; Classification of the Radiological Machine Learning-Based Quantitative Imaging Software With Predetermined Change Control Plan

This site displays a prototype of a “Web 2.0” version of the daily Federal Register. It is not an official legal edition of the Federal Register, and does not replace the official print version or the ...
IEEE

Quantum Machine Learning in Medical Image Analysis: From Diagnostics to Surgery Planning

Abstract: Quantum Machine Learning (QML) is an emerging, powerful paradigm at the intersection of quantum computing and artificial intelligence, with the potential to enhance medical image analysis.
Journal of Medical Internet Research

Digital Phenotyping for Adolescent Mental Health: Feasibility Study Using Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data

Objective: This study evaluated the feasibility of using a smartphone app to predict mental health risks in non-clinical adolescents by integrating active and passive data streams within a machine ...
RAPS

IMDRF drafts framework on best practices for using AI in medical devices

The International Medical Device Regulators Forum (IMDRF) has released a draft technical document to create a harmonized set of best practices in mitigating risks associated with the use of artificial ...
Fierce Healthcare

OpenEvidence rolls out AI medical coding feature

OpenEvidence released an artificial intelligence-powered medical coding feature embedded in its clinical AI assistant. The new feature, called Coding Intelligence, provides automatic Current ...
Fierce Healthcare

Health system AI adoption surges in 2026 with execs reporting increased ROI: survey

AI platform adoption didn’t just increase among systems implementing one platform, as 50% of respondents indicated their systems use three or more applications. (iStock/Getty Images Plus) Seventy-five ...
The Lancet

When to and when not to use machine learning in risk prediction models

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

Traditional machine learning in biomedical image analysis: before you go too deep

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
Microsoft

UniRG: Scaling medical imaging report generation with multimodal reinforcement learning

AI can be used to produce clinically meaningful radiology reports using medical images like chest x-rays. Medical image report generation can reduce reporting burden while improving workflow ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
MD&M East

How Human-Machine Interfaces Can Revolutionize Medical Device Usability

Medical devices are constantly changing and improving, adding new features to revolutionize patient care. Studies have shown that human-machine interfaces can help to improve medical device usability ...