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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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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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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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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Grade 2 subclinical hypothyroidism (G2SCH) is associated with an increased risk of various diseases but is rarely detected before symptom onset. This study aims to develop a machine learning-based prediction model for G2SCH using…
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Radiolucent foreign body aspiration (FBA) remains diagnostically challenging due to its subtle imaging signatures on chest CT scans, often leading to delayed or missed diagnoses. We present a deep learning model integrating MedpSeg, a…
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With a growing number of studies applying generative artificial intelligence (GAI) models for health purposes, reporting standards are being developed to guide authors in this space. We describe the currently available reporting guidelines that…
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Current self-supervised learning (SSL) methods for 3D medical imaging rely on simple pretext formulations and organ- or modality-specific datasets, limiting their generalizability and scalability. We present 3DINO, a cutting-edge SSL method adapted to 3D…
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Cardiovascular diseases remain the leading cause of death in developed countries. This study introduces deep learning ensembles for arrhythmia detection and atrial fibrillation (AF) recurrence prediction from electrocardiogram scans, supported by explainable artificial intelligence…
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