When a deep learning model is trained sequentially on different datasets, it often forgets the knowledge learned from previous data, a problem known as catastrophic forgetting. This damages the model's performance on diverse datasets, which is critic...
PURPOSE OF REVIEW: Increased incorporation of artificial intelligence in medicine has raised questions regarding how it can enhance efficiency in concert with providing accurate medical information without violating patient privacy. Pediatricians sho...
OBJECTIVE: Deep learning approaches have demonstrated significant potential in predicting temporal health events in recent years. However, existing methods have not fully leveraged the complex interactions among comorbidities and have overlooked imba...
OBJECTIVE: This study uses probabilistic independence to disentangle patient-specific sources of disease and their signatures in Electronic Health Record (EHR) data.
BACKGROUND: Phenotyping, the process of systematically identifying and classifying conditions within clinical data, is a crucial first step in any data science work involving Electronic Health Records (EHRs). Traditional approaches require extensive ...
BACKGROUND: Processing scanned documents in electronic health records (EHR) was one of the problem in hospital network information management systems (HNIMS). To overcome this difficulty, the complex interactions among natural language processing (NL...
Journal of the American Medical Informatics Association : JAMIA
Jun 1, 2025
OBJECTIVE: To develop a continual process for linking more comprehensive external mortality data to electronic health records (EHRs) for a large healthcare system, which can serve as a template for other healthcare systems.
IMPORTANCE: Individuals whose chronic pain is managed with opioids are at high risk of developing an opioid use disorder. Electronic health records (EHR) allow large-scale studies to identify a continuum of problematic opioid use, including opioid us...
IMPORTANCE: Clinical practice guidelines recommend suicide risk screening and assessment across behavioral health settings. The predictive accuracy of real-world clinician assessments for stratifying patients by risk of future suicidal behavior, howe...
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive manual labelli...
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