Predicting stroke severity of patients using interpretable machine learning algorithms.
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| Title: | Predicting stroke severity of patients using interpretable machine learning algorithms. |
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| Authors: | Sorayaie Azar A; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark.; Department of Computer Engineering, Urmia University, Urmia, Iran., Samimi T; Department of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran.; Health and Biomedical Informatics Research Center, Urmia University of Medical Sciences, Urmia, Iran., Tavassoli G; Department of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran.; Health and Biomedical Informatics Research Center, Urmia University of Medical Sciences, Urmia, Iran.; Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran., Naemi A; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark., Rahimi B; Department of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran.; Health and Biomedical Informatics Research Center, Urmia University of Medical Sciences, Urmia, Iran., Hadianfard Z; Department of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran., Wiil UK; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark., Nazarbaghi S; Department of Neurology, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran., Bagherzadeh Mohasefi J; SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark. j.bagherzadeh@urmia.ac.ir.; Department of Computer Engineering, Urmia University, Urmia, Iran. j.bagherzadeh@urmia.ac.ir., Lotfnezhad Afshar H; Department of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran. lotfnezhadafshar.h@umsu.ac.ir.; Health and Biomedical Informatics Research Center, Urmia University of Medical Sciences, Urmia, Iran. lotfnezhadafshar.h@umsu.ac.ir. |
| Source: | European journal of medical research [Eur J Med Res] 2024 Nov 14; Vol. 29 (1), pp. 547. Date of Electronic Publication: 2024 Nov 14. |
| Publication Type: | Evaluation Study; Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 9517857 Publication Model: Electronic Cited Medium: Internet ISSN: 2047-783X (Electronic) Linking ISSN: 09492321 NLM ISO Abbreviation: Eur J Med Res Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2047-783X |
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| DOI: | 10.1186/s40001-024-02147-1 |
