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인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축

PURPOSE: To construct a standard dataset of contrast-enhanced CT images of liver tumors to test the performance and safety of artificial intelligence (AI)-based algorithms for clinical decision support systems (CDSSs). MATERIALS AND METHODS: A consensus group of medical experts in gastrointestinal r...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432358/
https://www.ncbi.nlm.nih.gov/pubmed/36238394
http://dx.doi.org/10.3348/jksr.2020.0177
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description PURPOSE: To construct a standard dataset of contrast-enhanced CT images of liver tumors to test the performance and safety of artificial intelligence (AI)-based algorithms for clinical decision support systems (CDSSs). MATERIALS AND METHODS: A consensus group of medical experts in gastrointestinal radiology from four national tertiary institutions discussed the conditions to be included in a standard dataset. Seventy-five cases of hepatocellular carcinoma, 75 cases of metastasis, and 30–50 cases of benign lesions were retrieved from each institution, and the final dataset consisted of 300 cases of hepatocellular carcinoma, 300 cases of metastasis, and 183 cases of benign lesions. Only pathologically confirmed cases of hepatocellular carcinomas and metastases were enrolled. The medical experts retrieved the medical records of the patients and manually labeled the CT images. The CT images were saved as Digital Imaging and Communications in Medicine (DICOM) files. RESULTS: The medical experts in gastrointestinal radiology constructed the standard dataset of contrast-enhanced CT images for 783 cases of liver tumors. The performance and safety of the AI algorithm can be evaluated by calculating the sensitivity and specificity for detecting and characterizing the lesions. CONCLUSION: The constructed standard dataset can be utilized for evaluating the machine-learningbased AI algorithm for CDSS.
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spelling pubmed-94323582022-10-12 인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축 Taehan Yongsang Uihakhoe Chi Informatics & AI PURPOSE: To construct a standard dataset of contrast-enhanced CT images of liver tumors to test the performance and safety of artificial intelligence (AI)-based algorithms for clinical decision support systems (CDSSs). MATERIALS AND METHODS: A consensus group of medical experts in gastrointestinal radiology from four national tertiary institutions discussed the conditions to be included in a standard dataset. Seventy-five cases of hepatocellular carcinoma, 75 cases of metastasis, and 30–50 cases of benign lesions were retrieved from each institution, and the final dataset consisted of 300 cases of hepatocellular carcinoma, 300 cases of metastasis, and 183 cases of benign lesions. Only pathologically confirmed cases of hepatocellular carcinomas and metastases were enrolled. The medical experts retrieved the medical records of the patients and manually labeled the CT images. The CT images were saved as Digital Imaging and Communications in Medicine (DICOM) files. RESULTS: The medical experts in gastrointestinal radiology constructed the standard dataset of contrast-enhanced CT images for 783 cases of liver tumors. The performance and safety of the AI algorithm can be evaluated by calculating the sensitivity and specificity for detecting and characterizing the lesions. CONCLUSION: The constructed standard dataset can be utilized for evaluating the machine-learningbased AI algorithm for CDSS. The Korean Society of Radiology 2021-09 2021-08-05 /pmc/articles/PMC9432358/ /pubmed/36238394 http://dx.doi.org/10.3348/jksr.2020.0177 Text en Copyrights © 2021 The Korean Society of Radiology https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Informatics & AI
인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축
title 인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축
title_full 인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축
title_fullStr 인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축
title_full_unstemmed 인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축
title_short 인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축
title_sort 인공지능 기반 임상의학 결정 지원 시스템 의료기기의 성능 및 안전성 검증을 위한 간 종양 표준 데이터셋 구축
topic Informatics & AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432358/
https://www.ncbi.nlm.nih.gov/pubmed/36238394
http://dx.doi.org/10.3348/jksr.2020.0177
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