Transthoracic echocardiography (TTE), commonly used for initial screening of pulmonary hypertension (PH), often lacks sufficient accuracy. To address this gap, we developed and validated a multimodal fusion model for improved PH screening (MMF-PH). The…
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This study explored differences in COVID-19 infections and symptoms between Android and iOS users using data from the CoronaCheck app. This cross-sectional analysis included 23,063 global users (20,753 Android and 2310 iOS) from April…
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Digital phenotyping collects health data digitally, supporting early disease diagnosis and health management. This paper systematically reviews the diversity of research methods in digital phenotyping and its clinical benefits, while also focusing on its…
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We developed a practical framework to construct digital twins for predicting and optimizing triple-negative breast cancer (TNBC) response to neoadjuvant chemotherapy (NAC). This study employed 105 TNBC patients from the ARTEMIS trial (NCT02276443, registered…
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We developed and validated models to predict 1- and 2-week risk of non-elective hospitalization (NEH) and sepsis hospitalization following outpatient clinic, emergency department treat and release (EDTR), or hospitalization encounters. We employed data from…
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Aiming to reach the unreached, we developed a Dashboard pipeline incorporated with ChatGPT engine to effectively monitoring various disease metrics and trends and to inform necessary response strategies. This WHO Digital Public Good provides…
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The efficacy of telehealth Virtual Reality (VR) for chronic pain, a promising digital intervention, remains underexplored due to methodological challenges. In a 5-week crossover trial, we compared VR to matched audio content control in…
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As climate change threatens to destroy health gains, digital health provides infrastructure that is well-placed to offer patient-centred health insights. These insights are important to advance research to explore the intersection of climate and…
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Sepsis real-time prediction models (SRPMs) provide timely alerts and may improve patient outcomes but face limited clinical adoption due to inconsistent validation methods and potential biases. Comprehensive evaluation, including external full-window validation with model-…
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The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) supports large-scale research by enabling distributed network analyses. However, the breadth of its adoption in cancer research is not well understood. We conducted a…
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