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Diverging trajectories of trust in healthcare and on-line information seeking: what’s next with LLMs

Diverging trajectories of trust in healthcare and on-line information seeking: what’s next with LLMs

February 1, 2026February 1, 2026
Weekly Roundup – January 31, 2026

Weekly Roundup – January 31, 2026

January 31, 2026February 1, 2026
Embedding clinical intelligence to help close care gaps

Embedding clinical intelligence to help close care gaps

January 31, 2026January 31, 2026
Impact of Mobilization Facilitated by Wearable Device Enhanced Patient Monitoring/Electrophysiology Pod–Based Feedback on Postoperative Complications Following Colorectal Cancer Surgery: Randomized Controlled Trial

Impact of Mobilization Facilitated by Wearable Device Enhanced Patient Monitoring/Electrophysiology Pod–Based Feedback on Postoperative Complications Following Colorectal Cancer Surgery: Randomized Controlled Trial

January 31, 2026January 31, 2026
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Tag: medical imaging

Optimizing retinal images based carotid atherosclerosis prediction with explainable foundation models

Optimizing retinal images based carotid atherosclerosis prediction with explainable foundation models

October 1, 2025October 1, 2025npj Digital Medicine

Carotid atherosclerosis is a key predictor of cardiovascular disease (CVD), necessitating early detection. While foundation models (FMs) show promise in medical imaging, their optimal selection and fine-tuning strategies for classifying carotid atherosclerosis from retinal…

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Healthcare’s Unstructured Data Problem: The Case for Modernization

Healthcare’s Unstructured Data Problem: The Case for Modernization

September 15, 2025September 15, 2025HIT Consultant

Steve Leeper, VP Product Marketing at Datadobi

Like most other sectors operating in the digital economy, healthcare has become hugely reliant on unstructured data. It’s widely acknowledged that this data type, which doesn’t follow a…

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Medical Imaging Ecosystems: A New Model for AI Adoption and Interoperability

Medical Imaging Ecosystems: A New Model for AI Adoption and Interoperability

September 12, 2025September 13, 2025HIT Consultant

Jordan Bazinsky, CEO, Intelerad

The medical imaging industry is increasingly embracing a simple truth: there is strength in numbers. This is evident in the growing adoption of partnership ecosystems. This collaborative model brings technology companies…

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Health AI Revolutionizes Stroke Treatment Success

Health AI Revolutionizes Stroke Treatment Success

August 13, 2025August 13, 2025DistilINFO Hospital IT

Revolutionary AI Technology Transforms Emergency Care
Detroit-based Henry Ford Health has revolutionized stroke treatment by implementing cutting-edge artificial intelligence technology that dramatically reduces treatment times and saves lives. The healthcare system’s adoption of RapidAI, an…

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AI-driven preclinical disease risk assessment using imaging in UK biobank

AI-driven preclinical disease risk assessment using imaging in UK biobank

July 26, 2025July 26, 2025npj Digital Medicine

Identifying disease risk and detecting disease before clinical symptoms appear are essential for early intervention and improving patient outcomes. In this context, the integration of medical imaging in a clinical workflow offers a unique…

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Re-identification of patients from imaging features extracted by foundation models

Re-identification of patients from imaging features extracted by foundation models

July 22, 2025July 22, 2025npj Digital Medicine

Foundation models for medical imaging are a prominent research topic, but risks associated with the imaging features they can capture have not been explored. We aimed to assess whether imaging features from foundation models…

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HOPPR Launches New Chest Radiography Model with API Access

HOPPR Launches New Chest Radiography Model with API Access

July 17, 2025July 18, 2025HIT Consultant

What You Should Know: 

– HOPPR, a secure AI development platform for medical imaging announced the commercial release of its HOPPR Marie Curie Chest Radiography Foundation Model and fine-tuning API for binary classification, alongside inference…

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A perspective for adapting generalist AI to specialized medical AI applications and their challenges

A perspective for adapting generalist AI to specialized medical AI applications and their challenges

July 11, 2025July 11, 2025npj Digital Medicine

We introduce a framework to adapt large language models for medicine: (1) Modeling: breaking down medical workflows into manageable steps; (2) Optimization: optimizing model performance via advanced adaptations; and (3) System engineering: developing agent…

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SimonMed Imaging Launches AI-Enhanced Mammogram Services

SimonMed Imaging Launches AI-Enhanced Mammogram Services

July 7, 2025July 8, 2025HIT Consultant

What You Should Know: 

– SimonMed Imaging, one of the largest outpatient medical imaging providers in the United States, today announced the launch of Mammogram+ and Mammogram+ Heart, two new AI-enhanced mammogram services designed to…

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AI-Driven Diagnostics: The Future of Precision in Medical Imaging

AI-Driven Diagnostics: The Future of Precision in Medical Imaging

June 20, 2025June 20, 2025HIT Consultant

Thomas Kluz, Managing Director at Niterra Venture

During the past ten years, I’ve collaborated and invested in several innovative healthcare organizations, and I have realized that AI has extended beyond just being a supporting tool for medical purposes. It…

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The physical space of the hospital will be gradually digitized until virtually every object and sensor becomes part of the so-called 'Internet of Things.' These innovations can broadly be categorized as either clinical or experiential, though some will be both. Clinical innovations will involve gathering ever more "signals" from the patient (infrared, sound, electrophysiology, pulse-oximeter, facial expression, etc.) to be sifted in real time through machine-learning algorithms that will help physicians refine their understanding of diagnosis and prognosis in ways we can only imagine today. Experiential innovations will allow health systems and their partners to take a page from Netflix, using the engagement opportunity of the acute care episode to stream digital content to patients and families through TVs, tablets and their own devices from home.

Daniel Durand

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