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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: Natural Language Processing

AI assisted prediction of unplanned intensive care admissions using natural language processing in elective neurosurgery

AI assisted prediction of unplanned intensive care admissions using natural language processing in elective neurosurgery

August 27, 2025August 27, 2025npj Digital Medicine

Timely care in a specialised neuro-intensive therapy unit (ITU) reduces mortality and hospital stays. Planned admissions to ITU following surgery are safer than unplanned ones. However, post-operative care decisions remain subjective. This study used…

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ZeOmega Partners With Datycs to Optimize Prior Authorization

ZeOmega Partners With Datycs to Optimize Prior Authorization

August 21, 2025August 21, 2025HIT Consultant

What You Should Know:

–ZeOmega®, the leading population health management organization, today announced its partnership with Datycs, a leading provider of clinical AI/Natural Language Processing (NLP) solutions, to automate converting unstructured data from faxed documents…

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Multimodal machine learning for risk-stratified bundled payments in spinal surgery

Multimodal machine learning for risk-stratified bundled payments in spinal surgery

August 10, 2025August 10, 2025npj Digital Medicine

Accurate prediction of financial metrics in spine surgery is crucial as healthcare transitions to value-based care. While bundled payment models have succeeded in other orthopedic procedures, the heterogeneity of spinal surgery complicates their adoption….

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For Persivia, It Takes a Blend of AI Types to Address Value Based Care Efforts

For Persivia, It Takes a Blend of AI Types to Address Value Based Care Efforts

July 15, 2025July 16, 2025Healthcare IT Today

Mansoor Khan, like other health care transformers, wants AI to help clinicians “do the job better, faster, cheaper.” As CEO at Persivia, he recognizes that different types of AI are needed for different parts…

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Digital transformation with clinical alerts and personalized care systems in an integrated value based model

Digital transformation with clinical alerts and personalized care systems in an integrated value based model

July 8, 2025July 8, 2025npj Digital Medicine

Patient portals are widely available to facilitate self-service interactions, including appointment booking, offering convenience to users. Promoting clinically appropriate care pathways, however, is complex; portals must recognize patient intent while striving for an intuitive…

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Natural Language Processing Chatbot–Based Interventions for Improvement of Diet, Physical Activity, and Tobacco Smoking Behaviors: Systematic Review

Natural Language Processing Chatbot–Based Interventions for Improvement of Diet, Physical Activity, and Tobacco Smoking Behaviors: Systematic Review

June 11, 2025June 12, 2025JMIR mHealth and uHealth

Background: Empowered by the rapid development of artificial intelligence technology, chatbots have been increasingly used for the promotion of health-related behaviors to address the high demand for human resources in conventional behavioral interventions. However,…

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Applying AI in pediatric care requires careful consideration

Applying AI in pediatric care requires careful consideration

June 5, 2025June 5, 2025Healthcare IT news

While there are many similarities between the use of artificial intelligence in adult care and pediatrics, there are also some unique and important considerations for the latter, due to the complexity of health issues…

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Comparative analysis of natural language processing methodologies for classifying computed tomography enterography reports in Crohn’s disease patients

Comparative analysis of natural language processing methodologies for classifying computed tomography enterography reports in Crohn’s disease patients

May 30, 2025May 30, 2025npj Digital Medicine

Imaging is crucial to assess disease extent, activity, and outcomes in inflammatory bowel disease (IBD). Artificial intelligence (AI) image interpretation requires automated exploitation of studies at scale as an initial step. Here we evaluate…

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Viz.ai partners with Regeneron, Sanofi to study COPD tool

Viz.ai partners with Regeneron, Sanofi to study COPD tool

May 21, 2025May 21, 2025MobiHealthNews

AI-backed imaging and care coordination company Viz.ai is partnering with biotechnology company Regeneron and biopharmaceutical company Sanofi to deploy and study an AI-enabled workflow tool for COPD. Viz.ai offers a care coordination platform with more…

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Study combines NLP, conventional coding to improve dementia detection

Study combines NLP, conventional coding to improve dementia detection

May 20, 2025May 20, 2025MobiHealthNews

The National Centre for Healthy Ageing, a research institute by Monash University and Peninsula Health in Australia, has developed a new AI-driven method to efficiently identify dementia in hospitals. It researched ways to uplift dementia…

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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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