When MedAllies was founded in 2001, the healthcare landscape looked vastly different from what it does today. Long before the HITECH Act spurred the widespread digitization of medical records, the company set out with…
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Digital health tools such as remote patient monitoring (RPM) and digital health coaching (DHC) offer promising strategies for type 2 diabetes (T2D) management, yet little is known about how underserved Black adults experience these…
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Congenital and acquired heart disease affects approximately 1% of children worldwide, and right ventricular (RV) dysfunction is a common and complex manifestation in conditions such as congenital heart disease, pulmonary hypertension, and prematurity. Accurate…
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Australia unveils national cancer data framework and more briefs | Healthcare IT News
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P4 medicine (Predictive, Preventive, Personalized, and Participatory) offers a comprehensive approach to personalized healthcare, emphasizing both the transition from disease to wellness and the importance of preventive care. In this perspective, we propose a…
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Real-time prediction of short-term mortality risk in the intensive care unit (ICU) is often hampered by missing medical data. To address this, we developed RealMIP, an end-to-end framework leveraging generative model for the dynamic…
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Sjögren’s disease (SjD) is a common systemic autoimmune disease that remains difficult to diagnose early due to non-specific symptoms and lack of definitive biomarkers. This multicentre retrospective cohort study analysed data from 34,958 patients…
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Accurate detection of lung cancer from Computed Tomography (CT) scans is vital for improving patient survival but remains challenging for deep learning models, which struggle with scale variations of pulmonary nodules and the complex…
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Effective risk stratification is essential in clinical practice, enabling better resource allocation and improved patient outcomes. Although machine learning models have been widely used for risk prediction and stratification in electronic health record (EHR)…
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This study introduces a machine learning framework to predict effective antiviral combinations for influenza A. It identifies Pimodivir with Epinephrine or L-Adrenaline as synergistic agents, confirmed by experiments demonstrating increased binding affinity and viral…
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