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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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Category: npj Digital Medicine

Deep learning to assess microsatellite instability directly from histopathological whole slide images in endometrial cancer

Deep learning to assess microsatellite instability directly from histopathological whole slide images in endometrial cancer

May 29, 2024May 30, 2024npj Digital Medicine

Molecular classification, particularly microsatellite instability-high (MSI-H), has gained attention for immunotherapy in endometrial cancer (EC). MSI-H is associated with DNA mismatch repair defects and is a crucial treatment predictor. The NCCN guidelines recommend pembrolizumab…

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A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders

A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders

May 25, 2024May 25, 2024npj Digital Medicine

Step length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g., in clinic or real-world settings), however, the accuracy of current estimation methods is…

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A digital twin model incorporating generalized metabolic fluxes to identify and predict chronic kidney disease in type 2 diabetes mellitus

A digital twin model incorporating generalized metabolic fluxes to identify and predict chronic kidney disease in type 2 diabetes mellitus

May 24, 2024May 24, 2024npj Digital Medicine

We have developed a digital twin-based CKD identification and prediction model that leverages generalized metabolic fluxes (GMF) for patients with Type 2 Diabetes Mellitus (T2DM). GMF digital twins utilized basic clinical and physiological biomarkers…

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The three-year evolution of Germany’s Digital Therapeutics reimbursement program and its path forward

The three-year evolution of Germany’s Digital Therapeutics reimbursement program and its path forward

May 24, 2024May 25, 2024npj Digital Medicine

The 2019 German Digital Healthcare Act introduced the Digital Health Application program, known in German as ‘Digitale Gesundheitsanwendungen’ (DiGA). The program has established a pioneering model for integrating Digital Therapeutics (DTx) into a healthcare…

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Evaluation of stenoses using AI video models applied to coronary angiography

Evaluation of stenoses using AI video models applied to coronary angiography

May 24, 2024May 24, 2024npj Digital Medicine

The coronary angiogram is the gold standard for evaluating the severity of coronary artery disease stenoses. Presently, the assessment is conducted visually by cardiologists, a method that lacks standardization. This study introduces DeepCoro, a…

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Association of physical activity pattern and risk of Parkinson’s disease

Association of physical activity pattern and risk of Parkinson’s disease

May 23, 2024May 24, 2024npj Digital Medicine

Increasing evidence suggests an association between exercise duration and Parkinson’s disease. However, no high-quality prospective evidence exists confirming whether differences exist between the two modes of exercise, weekend warrior and equal distribution of exercise…

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Early adverse physiological event detection using commercial wearables: challenges and opportunities

Early adverse physiological event detection using commercial wearables: challenges and opportunities

May 23, 2024May 24, 2024npj Digital Medicine

Data from commercial off-the-shelf (COTS) wearables leveraged with machine learning algorithms provide an unprecedented potential for the early detection of adverse physiological events. However, several challenges inhibit this potential, including (1) heterogeneity among and…

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Virtual fitness buddy ecosystem: a mixed reality precision health physical activity intervention for children

Virtual fitness buddy ecosystem: a mixed reality precision health physical activity intervention for children

May 21, 2024May 21, 2024npj Digital Medicine

6–11-year-old children provide a critical window for physical activity (PA) interventions. The Virtual Fitness Buddy ecosystem is a precision health PA intervention for children integrating mixed reality technology to connect people and devices. A…

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Generalization—a key challenge for responsible AI in patient-facing clinical applications

Generalization—a key challenge for responsible AI in patient-facing clinical applications

May 21, 2024May 21, 2024npj Digital Medicine

Generalization – the ability of AI systems to apply and/or extrapolate their knowledge to new data which might differ from the original training data – is a major challenge for the effective and responsible…

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Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality

May 20, 2024May 20, 2024npj Digital Medicine

Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring…

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With respect to healthcare, I see digital transformation as a formula: simplified patient journey + streamlined employee workflow = a memorable experience. The ability to distill the patient touch points down to only what is necessary, make the behind-the-scenes workflow less cumbersome (reducing silos and friction points) and accelerate the entire throughput with carefully selected and complementary technology is the essence of digital transformation. Process is always upstream from technology, and any digital effort should take that into consideration.

Tom Barnett

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