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首页> Talanta> Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19.

Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19.

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作者： Gorkem,Tokgoz ^[1] ; K Kubra,Kirboga ^[1] ; Faik,Ozel ^[2] ; Serkan,Yucepur ^[3] ; Isa,Ardahanli ^[4] ; Rafig,Gurbanov ^[5]

作者单位： Department of Bioengineering, Faculty of Engineering, Bilecik Şeyh Edebali University, Bilecik, 11100, Turkey. ^[1] Department of Internal Medicine, Faculty of Medicine, Bilecik Şeyh Edebali University Bilecik, 11100, Turkey. ^[2] Department of Anesthesiology and Reanimation, Faculty of Medicine, Bilecik Şeyh Edebali University Bilecik, 11100, Turkey. ^[3] Department of Cardiology, Faculty of Medicine, Bilecik Şeyh Edebali University Bilecik, 11100, Turkey. ^[4] Department of Bioengineering, Faculty of Engineering, Bilecik Şeyh Edebali University, Bilecik, 11100, Turkey; Central Research Laboratory, Bilecik Şeyh Edebali University, Bilecik, 11100, Turkey. Electronic address: rafig.gurbanov@bilecik.edu.tr. ^[5]

关键词 Biomarker COVID-19 Explainable artificial intelligence FTIR Shapley explanations

主题词人类(Humans);人工智能(Artificial Intelligence);男(雄)性(Male);中年人(Middle Aged);危重病(Critical Illness);女(雌)性(Female);谱学, 傅里叶变换红外(Spectroscopy, Fourier Transform Infrared);老年人(Aged);免疫球蛋白G(Immunoglobulin G);成年人(Adult);糖基化(Glycosylation);疾病严重程度指数(Severity of Illness Index)

DOI 10.1016/j.talanta.2024.126652

PMID 39106646

发布时间 2024-08-30

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