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Prediction of Key Patient Outcome from Sentence and Word of Medical Text Records.

, , , , and . ClinicalNLP@COLING 2016, page 86-90. The COLING 2016 Organizing Committee, (2016)

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Explanation of Machine Learning Models Using Shapley Additive Explanation and Application for Real Data in Hospital., , , and . CoRR, (2021)Machine learning for classification of postoperative patient status using standardized medical data., , , , , , , , , and 1 other author(s). Comput. Methods Programs Biomed., (2022)Development of Machine Learning Prediction Models for Self-Extubation After Delirium Using Emergency Department Data., , , , , , and . MedInfo, volume 310 of Studies in Health Technology and Informatics, page 1001-1005. IOS Press, (2023)Explanation of machine learning models using shapley additive explanation and application for real data in hospital., , , and . Comput. Methods Programs Biomed., (2022)A Japanese Model of Disease Management., , , , , , , , , and . MedInfo, volume 129 of Studies in Health Technology and Informatics, page 1174-1178. IOS Press, (2007)Explanation of Machine Learning Models Using Improved Shapley Additive Explanation., , , and . BCB, page 546. ACM, (2019)Graph Clustering System for Text-Based Records in a Clinical Pathway., , , , and . MedInfo, volume 245 of Studies in Health Technology and Informatics, page 649-652. IOS Press, (2017)Prediction of Key Patient Outcome from Sentence and Word of Medical Text Records., , , , and . ClinicalNLP@COLING 2016, page 86-90. The COLING 2016 Organizing Committee, (2016)