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Evaluating a Natural Language Processing-Driven, AI-Assisted International Classification of Diseases, 10th Revision, Clinical Modification, Coding System for Diagnosis Related Groups in a Real Hospital Environment: Algorithm Development and Validation Study.

Hong-Jie DaiChen-Kai WangChien-Chang ChenChong-Sin LiouAn-Tai LuChia-Hsin LaiBo-Tsz ShainCheng-Rong KeWilliam Yu Chung WangTatheer Hussain MirMutiara SimanjuntakHao-Yun KaoMing-Ju TsaiVincent S Tseng
Published in: Journal of medical Internet research (2024)
An NLP-driven AI-assisted coding system can assist CCSs in ICD-10-CM coding by offering coding references via a user interface, demonstrating the potential to reduce the manual workload and expedite Tw-DRG assessment. Consistency in performance affirmed the effectiveness of the system in supporting CCSs in ICD-10-CM coding and the judgment of Tw-DRGs.
Keyphrases
  • machine learning
  • artificial intelligence
  • deep learning
  • randomized controlled trial
  • systematic review
  • healthcare
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  • emergency department
  • risk assessment
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  • human health