Dalton Shaull, Director of Digital Services, XVIVO Bio
In organ transplantation, timing isn’t just critical. It is the difference between life and death. Every transplant is a race against the clock, requiring precise coordination among…
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Get Well and RhythmX AI merge patient engagement and precision medicine | Healthcare IT News
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New episodes are released every two weeksThe Out of Programme Podcast shines a spotlight on clinicians who have ventured beyond the traditional path of clinical training to forge unique and unconventional careers. The series…
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Bent Philipson, Founder of Philosophy Care
There has never been a greater need for more comprehensive and compassionate approaches to elder care as countries struggle to support aging populations everywhere. Clinical and custodial frameworks still…
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Cage subsidence after oblique lumbar interbody fusion (OLIF) frequently causes poor outcomes, yet existing predictive models lack accuracy and applicability. This study leveraged the Least Absolute Shrinkage and Selection Operator (LASSO) regression to efficiently…
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Potentially malignant oral lesions are visible mucosal changes with risk of progressing to squamous cell carcinoma. These lesions are currently graded as no, mild, moderate, or severe dysplasia per WHO guidelines. While widely used,…
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Health human resource constraints in Canada have left millions of patients without timely access to primary care (PC), leading many to attend emergency departments (ED) to see a doctor. We evaluated changes in service…
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The Vatican convenes a Rome conference this week titled “AI and Medicine: The Challenge of Human Dignity,” where a church official warned of the risk of “transforming health and illness into mere numerical data…
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We propose metrics from information theory to characterize the clinical and operational dynamics of hospitals. Ergodicity, the equality of time- and space-averages within a dynamical system, ensures its stationarity. Surprisal, the log-inverse of probability,…
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Tricuspid regurgitation (TR) remains underdiagnosed due to the lack of effective screening tools. We developed a self-distilled and pre-trained transformer model for detecting TR (SPEED-TR) from electrocardiography. The model was trained using 466,149 electrocardiogram-echocardiogram…
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