This paper is in the following e-collection/theme issue:

Artificial Intelligence (2129) Machine Learning (2076) Clinical Information and Decision Making (1915) Artificial Intelligence in Surgery and Perioperative Medicine (43) Decision Support for Health Professionals (1539) Surgery, Trauma and Surgical Sciences (202) Tools, Programs and Algorithms (376) Postoperative Cognitive Dysfunction (POCD) (5) Postoperative Monitoring and Telemonitoring (190)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55046, first published .
A Supervised Explainable Machine Learning Model for Perioperative Neurocognitive Disorder in Liver-Transplantation Patients and External Validation on the Medical Information Mart for Intensive Care IV Database: Retrospective Study

A Supervised Explainable Machine Learning Model for Perioperative Neurocognitive Disorder in Liver-Transplantation Patients and External Validation on the Medical Information Mart for Intensive Care IV Database: Retrospective Study

A Supervised Explainable Machine Learning Model for Perioperative Neurocognitive Disorder in Liver-Transplantation Patients and External Validation on the Medical Information Mart for Intensive Care IV Database: Retrospective Study

Authors of this article:

Zhendong Ding1 Author Orcid Image ;   Linan Zhang1 Author Orcid Image ;   Yihan Zhang1 Author Orcid Image ;   Jing Yang1 Author Orcid Image ;   Yuheng Luo2 Author Orcid Image ;   Mian Ge1 Author Orcid Image ;   Weifeng Yao1 Author Orcid Image ;   Ziqing Hei1 Author Orcid Image ;   Chaojin Chen1 Author Orcid Image
Article Authors Cited by (24) Tweetations Metrics

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  10. Hussain S, Degang X, Shah P, Khan H, Zeb A. AlzFormer: Multi-modal framework for Alzheimer’s classification using MRI and graph-embedded demographics guided by adaptive attention gating. Computerized Medical Imaging and Graphics 2025;124:102638 View
  11. Aldosari F, El-kott A, AlShehri M, Singh N, Negm S, Alarousi H, Ghamry H, Morsy K, Karmakar B. Copper nanoparticles anchored on guar gum modified magnetic nanoparticles: Investigation of their catalytic efficiency in C-S coupling reactions and their anti-hepatitis cancer properties. Journal of Organometallic Chemistry 2025;1040:123807 View
  12. Ogundokun R, Owolawi P, Tu C, van Wyk E. Autoencoder-Assisted Stacked Ensemble Learning for Lymphoma Subtype Classification: A Hybrid Deep Learning and Machine Learning Approach. Tomography 2025;11(8):91 View
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  14. Demir S, Selvitopi H, Selvitopi Z. An early and accurate diagnosis and detection of the coronary heart disease using deep learning and machine learning algorithms. Journal of Big Data 2025;12(1) View
  15. Jones J, Sakai T. The Potential Impacts of Artificial Intelligence on Preoperative Optimization and Predicting Risks of Morbidity and Mortality: A Narrative Focused Review. A&A Practice 2025;19(10):e02061 View
  16. Saeidi M, Hassanzadeh G, Rouhollah F, Mokhtari T. Chronic Stress Disrupts Immune and Endocrine Axis, Inducing Persistent Behavioral Impairments in Male Rats: In Silico and In Vivo Insights. Neurochemical Research 2025;50(5) View
  17. Guo K, Huang P, Zhang J, Zhang B, Li L, Li J. Using glucocorticoid receptor-related genes to create and validate a survival model predicting gastric cancer. Computational Biology and Chemistry 2026;120:108726 View
  18. Țica O, Champsi A, Duan J, Țica O. Artificial Intelligence in the Diagnosis and Management of Atrial Fibrillation. Diagnostics 2025;15(20):2561 View
  19. Li Z, Wang L, Zhang X, Wu A, Liu T. Integration of machine learning and large language models for screening and identifying key risk factors of acute kidney injury after cardiac surgery. Frontiers in Medicine 2025;12 View
  20. Zhang N, Liu Y, Guan Y. Piceatannol ameliorates the memory ability and cognitive behavior in Alzheimer’s disease mice. Neurological Research 2025:1 View
  21. Kevin M, Varadharajan S, Praveen Kumar P, Swaminathan S, Dharshini R. Mitochondrial-Based Nanomedicine in Treatment of Liver Cancer. Molecular Biotechnology 2025 View
  22. Faizal W, Mazlan N, Shaukat S, Khor C, Haidiezul A, Syafiq A. The Convergence of Computational Fluid Dynamics and Machine Learning in Oncology: A Review. Computer Modeling in Engineering & Sciences 2025;144(2):1335 View
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  24. Lei H, Li Z, Deng J, Lei H, Li H, Ding Z. Electroacupuncture pretreatment ameliorates anesthesia and surgery-induced cognitive dysfunction in aged rats: insights from gut microbiota modulation. Frontiers in Microbiology 2025;16 View