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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: model

Stanford Medicine's ChatEHR expedites the chart review process

Stanford Medicine’s ChatEHR expedites the chart review process

June 9, 2025June 10, 2025MobiHealthNews

ChatEHR, AI software developed at Stanford Medicine, is speeding up chart reviews by permitting clinicians to ask questions about medical records.Similar to how you can chat with a large language model like GPT-4, Stanford Health…

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New 'ChatEHR' tool enables clinical conversation at Stanford

New ‘ChatEHR’ tool enables clinical conversation at Stanford

June 9, 2025June 9, 2025Healthcare IT news

Physicians, nurses and other clinicians at Stanford Health Care are now able to interact directly with electronic health records, via a new software tool known as ChatEHR.WHY IT MATTERSThe tool, built by data scientists…

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Foundation versus domain-specific models for left ventricular segmentation on cardiac ultrasound

Foundation versus domain-specific models for left ventricular segmentation on cardiac ultrasound

June 6, 2025June 6, 2025npj Digital Medicine

The Segment Anything Model (SAM) was fine-tuned on the EchoNet-Dynamic dataset and evaluated on external transthoracic echocardiography (TTE) and Point-of-Care Ultrasound (POCUS) datasets from CAMUS (University Hospital of St Etienne) and Mayo Clinic (99…

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Machine learning to predict penumbra core mismatch in acute ischemic stroke using clinical note data

Machine learning to predict penumbra core mismatch in acute ischemic stroke using clinical note data

June 6, 2025June 6, 2025npj Digital Medicine

In acute ischemic stroke due to large-vessel occlusion (AIS-LVO), late-window endovascular thrombectomy (EVT) decisions depend on penumbra-to-core (P:C) mismatch from computed tomographic perfusion (CTP). We developed multiple machine learning (ML) models to predict P:C…

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Gleneagles Hospital Hong Kong adopts LLM-based clinical solutions for new day centre and more briefs

Gleneagles Hospital Hong Kong adopts LLM-based clinical solutions for new day centre and more briefs

June 6, 2025June 6, 2025Healthcare IT news

New day centre in Hong Kong to roll out clinical LLM, remote monitoring solutionsGleneagles Hospital Hong Kong is collaborating with two startups to integrate AI-powered clinical solutions at its new day procedure centre.
According to the…

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A “True Lifecycle Approach” towards governing healthcare AI with the GCC as a global governance model

A “True Lifecycle Approach” towards governing healthcare AI with the GCC as a global governance model

June 6, 2025June 6, 2025npj Digital Medicine

This paper proposes a “True Lifecycle Approach” (TLA) towards governing healthcare AI. The TLA governance model embeds core healthcare law principles—like informed consent, liability, and patient rights—throughout AI’s development, deployment, and use. Unlike narrow…

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Identifying and mitigating algorithmic bias in the safety net

Identifying and mitigating algorithmic bias in the safety net

June 5, 2025June 5, 2025npj Digital Medicine

Algorithmic bias occurs when predictive model performance varies meaningfully across sociodemographic classes, exacerbating systemic healthcare disparities. NYC Health + Hospitals, an urban safety net system, assessed bias in two binary classification models in our…

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Medical AI Breakthrough Changes Patient Care

Medical AI Breakthrough Changes Patient Care

June 4, 2025June 4, 2025DistilINFO Hospital IT

Healthcare AI Market Experiences Unprecedented Growth
The healthcare artificial intelligence landscape is experiencing unprecedented growth as major technology companies unveil groundbreaking platforms designed to revolutionize medical care. Recent announcements from industry leaders demonstrate how AI…

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AI project to predict health outcomes paused over GP data concern

AI project to predict health outcomes paused over GP data concern

June 4, 2025June 4, 2025Digital Health

NHS England has paused development of a generative AI model capable of predicting future health outcomes after doctors raised concerns about the use of GP patient data.
The model, called Foresight, trained on de-identified NHS…

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FDA introduces 'Elsa,' a genAI tool to drive efficiency

FDA introduces ‘Elsa,’ a genAI tool to drive efficiency

June 3, 2025June 3, 2025Healthcare IT news

The U.S. Food and Drug Administration on Monday announced the launch of a new generative AI technology that agency leaders said will help its employees do their jobs more efficiently.WHY IT MATTERSThe tool, called…

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The vaccine rollout process is a classic case study for successful projects requiring "people, process and technology." In this equation, the technology infrastructure of an electronic health record and network connectivity seem to be sufficient at most health systems and communities to support the cause. As a result, the most crucial elements to enable success is the project leadership and teamwork amongst all segments of the healthcare delivery system (people and process).

Michael Restuccia

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