Chronic diseases are gradually becoming the main threat to human health. By designing an efficient hospital management platform to quickly identify the corresponding chronic diseases, it can effectively reduce the labor cost, improve the accuracy of ...
Antimicrobial resistance and infection control
May 29, 2021
BACKGROUND: Environmental surface decontamination is a crucial tool to prevent the spread of infections in hospitals. However, manual cleaning and disinfection may be insufficient to eliminate pathogens from contaminated surfaces. Ultraviolet-C (UV-C...
Early identification of resource needs is instrumental in promoting efficient hospital resource management. Hospital information systems, and electronic health records (EHR) in particular, collect valuable demographic and clinical patient data from t...
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
May 17, 2021
Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains. However, these architectures have been limited in their ability to support complex prediction problems using insurance claims data, su...
It is well known that information technology (IT) can play a pivotal role in enhancing healthcare quality and patient safety. The use of computational science to enhance the capabilities of hospital information systems helps deliver enhanced healthca...
There is limited literature examining the accuracy of the VITEK 2 Advanced Expert System (AES) in characterisation of β-lactamase resistance patterns. We present a prospective single centre study to better ascertain the performance characteristics of...
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for...
OBJECTIVE: Machine learning (ML) algorithms are now widely used in predicting acute events for clinical applications. While most of such prediction applications are developed to predict the risk of a particular acute event at one hospital, few effort...
Journal of the American College of Surgeons
Apr 5, 2021
BACKGROUND: Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. To...
OBJECTIVE: The present study aimed to verify the classification performance of deep learning (DL) models for diagnosing fractures of the mandibular condyle on panoramic radiographs using data sets from two hospitals and to compare their internal and ...
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