A little less than a year ago, the U.S. Department of Veteran Affairs announced its Veteran Interoperability Pledge – an effort to boost information exchange between its own facilities and participating health systems, with…
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News
An 18-month study by Toronto’s St. Michael’s Hospital finds that its use of the Chartwatch AI system that predicts patient deterioration was associated with a 26% drop in unexpected deaths. The system was developed…
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This paper focuses on how regulatory bodies respond to artificial intelligence (AI)-enabled medical devices. To achieve this, we present a comparative overview of the United States (USA), European Union (EU), and China. Our search…
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There's so much stuff that is being unlocked from an AI and technology perspective to reduce the time to more effective therapies, which I think will fundamentally change how our medicine and drugs are…
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What You Should Know:
– Dandelion Health, a real-world data (RWD) and clinical AI platform, today announced findings from a study that suggests GLP-1 medications may be effective in preventing cardiovascular disease (CVD) in a…
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Pharmacotherapy guidelines for type 2 diabetes (T2D) emphasize patient-centered care, but applying this approach effectively in outpatient practice remains challenging. Data-driven treatment optimization approaches could enhance individualized T2D management, but current approaches cannot account…
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E-mental health (EMH) interventions gain increasing importance in the treatment of mental health disorders. Their outpatient efficacy is well-established. However, research on EMH in inpatient settings remains sparse and lacks a meta-analytic synthesis. This…
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Traditional healthcare delivery models face mounting pressure from rising costs, increasing demand, and a growing environmental footprint. Hospital at Home (HaH) has been proposed as a potential solution, offering care at home through in-person,…
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We aimed to identify and characterise behavioural profiles in patients at high risk of SCD, by using deep representation learning of day-to-day behavioural recordings. We present a pipeline that employed unsupervised clustering on low-dimensional…
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Risk adjustment is often necessary for outcome quality indicators (QIs) to provide fair and accurate feedback to healthcare professionals. However, traditional risk adjustment models are generally oversimplified and not equipped to disentangle complex factors…
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