STUDY OBJECTIVE: This study aimed to (1) develop and validate a natural language processing model to identify the presence of pulmonary embolism (PE) based on real-time radiology reports and (2) identify low-risk PE patients based on previously valid...
OBJECTIVE: Major depressive disorder (MDD) is linked to a 61% increased risk of emergency department (ED) visits and frequent ED usage. Collaborative care management (CoCM) models target MDD treatment in primary care, but how best to prioritize patie...
This research aimed to examine the effectiveness of artificial intelligence applications in asthma and chronic obstructive pulmonary disease (COPD) outpatient treatment support in terms of patient health and public costs. The data obtained in the res...
Studies in health technology and informatics
39176966
Diabetes mellitus (DM) is a significant public health issue in Germany, affecting 8 million individuals, with projections suggesting a substantial increase in the following years. Diabetic Foot Syndrome (DFS), leading to mobility issues and limb ampu...
BACKGROUND: The use of technologies has had a significant impact on patient safety and the quality of care and has increased globally. In the literature, it has been reported that people die annually due to adverse events (AEs), and various methods e...
BACKGROUND/OBJECTIVES: Child acute malnutrition is a global public health problem, affecting 45 million children under 5 years of age. The World Health Organization recommends monitoring weight gain weekly as an indicator of the correct treatment. Ho...
The Journal of antimicrobial chemotherapy
39351986
OBJECTIVE: This study aimed to conduct a scoping review of machine learning (ML) techniques in outpatient parenteral antimicrobial therapy (OPAT) for predicting adverse outcomes and to evaluate their validation, implementation and potential barriers ...
PURPOSE OF REVIEW: Prudent integration of artificial intelligence (AI) into outpatient urology has already begun to revolutionize clinical workflows, improve administrative efficiency, and automate mundane and laborious tasks in the clinic setting.
BACKGROUND: Allergic rhinitis is a common disease that can affect the health of patients and bring huge social and economic burdens. In this study, we developed a model to predict the incidence rate of allergic rhinitis so as to provide accurate info...