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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: Digital medicine

Advancing breast, lung and prostate cancer research with federated learning. A systematic review

Advancing breast, lung and prostate cancer research with federated learning. A systematic review

May 27, 2025May 27, 2025npj Digital Medicine

Federated learning (FL) is advancing cancer research by enabling privacy-preserving collaborative training of machine learning (ML) models on diverse, multi-centre data. This systematic review synthesises current knowledge on state-of-the-art FL in oncology, focusing on…

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Situating governance and regulatory concerns for generative artificial intelligence and large language models in medical education

Situating governance and regulatory concerns for generative artificial intelligence and large language models in medical education

May 27, 2025May 27, 2025npj Digital Medicine

Generative artificial intelligence (GenAI) and large language models represent gains in educational efficiency and personalisation of learning. These are balanced against the considerations of the learning process, authentic assessment, and academic integrity. A pedagogical…

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A distributional reinforcement learning model for optimal glucose control after cardiac surgery

A distributional reinforcement learning model for optimal glucose control after cardiac surgery

May 27, 2025May 27, 2025npj Digital Medicine

This study introduces Glucose Level Understanding and Control Optimized for Safety and Efficacy (GLUCOSE), a distributional offline reinforcement learning algorithm for optimizing insulin dosing after cardiac surgery. Trained on 5228 patients, tested on 920,…

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Multicentre evaluation of deep learning CT autosegmentation of the head and neck region for radiotherapy

Multicentre evaluation of deep learning CT autosegmentation of the head and neck region for radiotherapy

May 27, 2025May 27, 2025npj Digital Medicine

This is a multi-institutional study to evaluate a head-and-neck CT auto-segmentation software across seven institutions globally. 11 lymph node levels and 7 organs-at-risk contours were evaluated in a two-phase study design. Time savings were…

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A systematic review of clinicians’ acceptance and use of clinical decision support systems over time

A systematic review of clinicians’ acceptance and use of clinical decision support systems over time

May 26, 2025May 26, 2025npj Digital Medicine

Existing reviews have identified factors influencing Clinical Decision Support (CDS) adoption by clinicians in practice but overlook the dynamic and evolving nature of technology and users’ needs over time. This review aimed to identify…

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Agile evaluation including two pragmatic trials on the uptake of a digital screening service

Agile evaluation including two pragmatic trials on the uptake of a digital screening service

May 26, 2025May 26, 2025npj Digital Medicine

Digital screening may divert lower-risk persons to lower-cost online screening, or offer higher-risk non-responders a more acceptable alternative. Population-based uptake estimates are lacking. We conducted four studies within four weeks by inviting 1700 Londoners…

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Approved trends and product characteristics of digital therapeutics in four countries

Approved trends and product characteristics of digital therapeutics in four countries

May 26, 2025May 26, 2025npj Digital Medicine

Digital therapeutics (DTx) provide innovative treatment options. In this study, we identified and compared approved DTx in China, the US, Germany, and Belgium. In total, 507 DTx applications were identified (US, 192; China, 235;…

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Advancing efficacy prediction for electronic health records based emulated trials in repurposing heart failure therapies

Advancing efficacy prediction for electronic health records based emulated trials in repurposing heart failure therapies

May 24, 2025May 25, 2025npj Digital Medicine

The complexities inherent in EHR data create discrepancies between real-world evidence and RCTs, posing substantial challenges in determining whether a treatment is likely to have a beneficial impact compared to the standard of care…

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Enhanced staging of renal cell carcinoma using tumor morphology features: model development and multi-source validation

Enhanced staging of renal cell carcinoma using tumor morphology features: model development and multi-source validation

May 24, 2025May 24, 2025npj Digital Medicine

Preoperative detection of pT3a invasion in non-metastatic renal cell carcinoma (RCC) remains challenging with CT. This study developed and validated radiomic models using preoperative CT to identify pT3a invasions. Six models were trained and…

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Classification grid and evidence matrix for evaluating digital medical devices under the European union landscape

Classification grid and evidence matrix for evaluating digital medical devices under the European union landscape

May 24, 2025May 24, 2025npj Digital Medicine

A uniform and harmonised taxonomy of Digital Medical Devices (DMDs) and their evidence-based evaluation are essential to ensure their integration into healthcare systems across the European Union (EU). As part of the Taskforce for…

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The most promising technology is AI combined with what we call "digital endpoints" for each service we provide. Digital endpoints are technologies like online scheduling, asynchronous video visits, and voice and application programming interfaces. The combination of AI and these endpoints mean that we can enable more sophisticated navigation, new business models, reduce friction and improve care delivery.

Aaron Martin

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