Chia Nan University of Pharmacy & Science Institutional Repository:Item 310902800/34455
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    標題: A Real-Time Artificial Intelligence-Assisted System to Predict Weaning from Ventilator Immediately after Lung Resection Surgery
    作者: Chang, Ying-Jen
    Hung, Kuo-Chuan
    Wang, Li-Kai
    Yu, Chia-Hung
    Chen, Chao-Kun
    Tay, Hung-Tze
    Wang, Jhi-Joung
    Liu, Chung-Feng
    貢獻者: Chi Mei Med Ctr, Dept Anesthesiol
    Chang Jung Christian Univ, Coll Hlth Sci
    Chia Nan Univ Pharm & Sci, Gen Educ Ctr
    Chi Mei Med Ctr, Dept Thorac Surg
    Chi Mei Med Ctr, Dept Intens Care Med
    Chi Mei Med Ctr, Dept Med Res
    Chi Mei Med Ctr, Dept Med Res, Ctr Big Med Data & Artificial Intelligence Comp
    關鍵字: lung resection
    pulmonary function test
    artificial intelligence
    machine learning
    pre-anesthetic consultation
    staged weaning
    日期: 2021
    上傳時間: 2023-11-11 11:53:44 (UTC+8)
    出版者: MDPI
    摘要: Assessment of risk before lung resection surgery can provide anesthesiologists with information about whether a patient can be weaned from the ventilator immediately after surgery. However, it is difficult for anesthesiologists to perform a complete integrated risk assessment in a time-limited pre-anesthetic clinic. We retrospectively collected the electronic medical records of 709 patients who underwent lung resection between 1 January 2017 and 31 July 2019. We used the obtained data to construct an artificial intelligence (AI) prediction model with seven supervised machine learning algorithms to predict whether patients could be weaned immediately after lung resection surgery. The AI model with Naive Bayes Classifier algorithm had the best testing result and was therefore used to develop an application to evaluate risk based on patients' previous medical data, to assist anesthesiologists, and to predict patient outcomes in pre-anesthetic clinics. The individualization and digitalization characteristics of this AI application could improve the effectiveness of risk explanations and physician-patient communication to achieve better patient comprehension.
    關聯: INT J ENV RES PUB HE, v.18, n.5, pp.2713
    显示于类别:[通識教育中心] 期刊論文

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