Artificial intelligence models analyzing speech show remarkable promise for identifying cognitive decline, achieving performance comparable to clinical assessments. However, their “black box” nature poses significant barriers to clinical adoption, as healthcare professionals require transparent…
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Wearable and health app data hold significant potential for healthcare and research, yet fragmented consent mechanisms create challenges for ethical, transparent, and user-controlled data sharing. We describe a centralised consent management system with a…
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The effectiveness of digital health management (DM) in post-discharge care for patients with coronary artery disease (CAD) remains insufficiently explored, particularly across public health emergencies. A total of 24,129 patients with CAD enrolled in…
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Rare diseases (RD) affect 3.5–5.9% of the global population, yet patients often endure a diagnostic odyssey averaging around 5–6 years, navigating multiple specialties and referrals. This study investigates the use of information content (IC)…
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Crystal Lennartz, President, Health Mart & Health Mart Atlas
Consumers today can get everything on demand and online, from groceries, to streaming content, to their prescriptions. Pharmacy digital capabilities, along with the ability to obtain…
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Many workforces are exposed to traumatic events which can precipitate the development of depression, anxiety and posttraumatic stress symptoms. This randomized controlled trial aimed to evaluate if an app-based version of the Skills for…
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Marketing Leadership and Strategic Vision
Ann Arbor-based Michigan Medicine’s marketing department is emphasizing its strong brand while “not resting on our laurels,” according to its new chief communication and marketing officer. Christine Woolsey, who assumed…
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Multimodal models have enabled the integration of digital pathology, radiology, clinical information, and omics data to enhance Colorectal cancer (CRC) care. This systematic review critically appraises Multimodal digital pathology techniques applied in CRC, their…
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Clinical decision-making often simplifies continuous risk data into discrete levels using round-number thresholds. These simplifications can distort risk assessments. To systematically uncover these distortions, we develop an interpretable machine learning model that identifies anomalies…
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Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are critical clinical events that necessitate prompt intervention, yet their detection remains challenging in primary care, especially in resource-limited regions where a lack of awareness leads…
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