Journal of the American Medical Informatics Association : JAMIA
Aug 7, 2015
OBJECTIVE: Hospitals are challenged to provide timely patient care while maintaining high resource utilization. This has prompted hospital initiatives to increase patient flow and minimize nonvalue added care time. Real-time demand capacity managemen...
BACKGROUND: Artificial neural networks (ANNs) can be used to develop predictive tools to enable the clinical decision-making process. This study aimed to investigate the use of an ANN in predicting the outcomes from enhanced recovery after colorectal...
BACKGROUND: Electronic medical record (EMR) systems have become widely used throughout the world to improve the quality of healthcare and the efficiency of hospital services. A bilingual medical lexicon of Chinese and English is needed to meet the de...
BMC medical informatics and decision making
May 6, 2015
BACKGROUND: In this study we implemented and developed state-of-the-art machine learning (ML) and natural language processing (NLP) technologies and built a computerized algorithm for medication reconciliation. Our specific aims are: (1) to develop a...
BACKGROUND: The Outpatient Arthroplasty Risk Assessment (OARA) Score was developed to risk-stratify patients for safe same-day discharge outpatient total joint arthroplasty (TJA). It has demonstrated predictive ability for length of stay in primary T...
OBJECTIVE: Postpartum depression (PPD) is a major contributor to postpartum morbidity and mortality. Beyond efforts at routine screening, risk stratification models could enable more targeted interventions in settings with limited resources. The auth...
Journal of neuroengineering and rehabilitation
May 26, 2025
In recent years, the fusion of the medical and computer science domains has gained significant traction in the scientific research landscape. Progress in both fields has enabled the generation of a vast amount of data used for making predictions and ...
This study aims to describe implementing a SNOMED CT-coded health problem (HP) list at Hospital Clínic de Barcelona. The project focuses on enhancing the accuracy and efficiency of clinical coding by automating the process from patient admission, whi...
Early identification of patients who require onward referral to social care can prevent delays to discharge from hospital. We introduce an explainable machine learning (ML) model to identify potential social care needs at the first point of admission...
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