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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: LLMs

Medical foundation large language models for comprehensive text analysis and beyond

Medical foundation large language models for comprehensive text analysis and beyond

March 5, 2025npj Digital Medicine

Recent advancements in large language models (LLMs) show significant potential in medical applications but are hindered by limited specialized medical knowledge. We present Me-LLaMA, a family of open-source medical LLMs integrating extensive domain-specific knowledge…

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Evaluating base and retrieval augmented LLMs with document or online support for evidence based neurology

Evaluating base and retrieval augmented LLMs with document or online support for evidence based neurology

March 4, 2025May 18, 2025npj Digital Medicine

Effectively managing evidence-based information is increasingly challenging. This study tested large language models (LLMs), including document- and online-enabled retrieval-augmented generation (RAG) systems, using 13 recent neurology guidelines across 130 questions. Results showed substantial variability….

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Assessing and alleviating state anxiety in large language models

Assessing and alleviating state anxiety in large language models

March 3, 2025March 4, 2025npj Digital Medicine

The use of Large Language Models (LLMs) in mental health highlights the need to understand their responses to emotional content. Previous research shows that emotion-inducing prompts can elevate “anxiety” in LLMs, affecting behavior and…

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Developing a named entity framework for thyroid cancer staging and risk level classification using large language models

Developing a named entity framework for thyroid cancer staging and risk level classification using large language models

March 1, 2025March 2, 2025npj Digital Medicine

We developed a named entity (NE) framework for information extraction from semi-structured clinical notes retrieved from The Cancer Genome Atlas—Thyroid Cancer (TCGA-THCA) database and examined Large Language Models (LLMs) strategies to classify the 8th…

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Chinese health players begin integrating DeepSek

Chinese health players begin integrating DeepSek

February 24, 2025March 2, 2025Healthcare IT news

Health ecosystem players in China are starting to adopt generative AI models by DeepSek, a new competitor to OpenAI.Recently, NASDAQ-listed e-commerce platform Akso Health Group, which is expanding to medical technology, announced the integration…

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An active inference strategy for prompting reliable responses from large language models in medical practice

An active inference strategy for prompting reliable responses from large language models in medical practice

February 22, 2025March 2, 2025npj Digital Medicine

Continuing advances in Large Language Models (LLMs) are transforming medical knowledge access across education, training, and treatment. Early literature cautions their non-determinism, potential for harmful responses, and lack of quality control. To address these…

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Comparing Large Language Models in Healthcare - Mayo Clinic Platform

Comparing Large Language Models in Healthcare – Mayo Clinic Platform

February 18, 2025February 19, 2025Digital Health Frontier

Given their tendency to invent “facts,” several researchers have begun comparing their strengths and weaknesses.

By John Halamka, M.D., President, Mayo Clinic Platform and Paul Cerrato, MA, senior research analyst and communications specialist, Mayo Clinic…

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Leveraging large language models for academic conference organization

Leveraging large language models for academic conference organization

February 14, 2025February 15, 2025npj Digital Medicine

We piloted using Large Language Models (LLMs) for organizing AMIA 2024 Informatics Summit. LLMs were prompt engineered to develop algorithms for reviewer assignments, group presentations into sessions, suggest session titles, and provide one-sentence summaries…

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Benchmarking the diagnostic performance of open source LLMs in 1933 Eurorad case reports

Benchmarking the diagnostic performance of open source LLMs in 1933 Eurorad case reports

February 12, 2025February 12, 2025npj Digital Medicine

Recent advancements in large language models (LLMs) have created new ways to support radiological diagnostics. While both open-source and proprietary LLMs can address privacy concerns through local or cloud deployment, open-source models provide advantages…

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The foundational capabilities of large language models in predicting postoperative risks using clinical notes

The foundational capabilities of large language models in predicting postoperative risks using clinical notes

February 11, 2025February 12, 2025npj Digital Medicine

Clinical notes recorded during a patient’s perioperative journey holds immense informational value. Advances in large language models (LLMs) offer opportunities for bridging this gap. Using 84,875 preoperative notes and its associated surgical cases from…

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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).

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