Polskie Archiwum Medycyny Wewnętrznej
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Pol. Arch. Med. Wewn. · May 2024
Comparative StudyUnattended automatic blood pressure measurements versus conventional office readings in predicting hypertension-mediated organ damage.
Hypertension is a leading cardiovascular risk factor. Accurate blood pressure (BP) measurement is pivotal in hypertension diagnosis and management. Conventional office blood pressure measurements (OBPMs) are error‑prone, exacerbated by the white‑coat effect. Unattended automated office blood pressure measurement (UAOBPM) is emerging as an alternative, mitigating the white‑coat effect. However, its ability to predict hypertension‑mediated organ damage (HMOD) remains disputable. ⋯ The UAOBPM did not prove superior to OBPM in predicting HMOD. Further research is warranted to determine the role of UAOBPM in clinical practice.
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Pol. Arch. Med. Wewn. · May 2024
Comparative StudyA comparison of interpretable XGBoost and artificial neural network model for the prediction of severe acute pancreatitis.
Acute pancreatitis (AP) that progresses to persistent organ failure is referred to as severe acute pancreatitis (SAP). It is a condition associated with a relatively high mortality. A prediction model that would facilitate early recognition of patients at risk for SAP is crucial for improvement of patient prognosis. ⋯ An interpretable XGBoost model showed better discriminatory efficiency for predicting SAP than the ANN model, and could be used in clinical practice to identify patients at risk for SAP.
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Pol. Arch. Med. Wewn. · May 2024
Practical use case of natural language processing for observational clinical research data retrieval from electronic health records: AssistMED project.
Electronic health records (EHRs) contain data valuable for clinical research. However, they are in textual format and require manual encoding to databases, which is a lengthy and costly process. Natural language processing (NLP) is a computational technique that allows for text analysis. ⋯ NLP utilization in EHRs may accelerate data acquisition and provide accurate information for retrospective studies.