Development and multi‐institutional validation of an artificial intelligence‐based diagnostic system for gastric biopsy
| العنوان: | Development and multi‐institutional validation of an artificial intelligence‐based diagnostic system for gastric biopsy |
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| المؤلفون: | Hiroyuki, Abe, Yusuke, Kurose, Shusuke, Takahama, Ayako, Kume, Shu, Nishida, Miyako, Fukasawa, Yoichi, Yasunaga, Tetsuo, Ushiku, Youichiro, Ninomiya, Akihiko, Yoshizawa, Kohei, Murao, Shin'ichi, Sato, Masaru, Kitsuregawa, Tatsuya, Harada, Masanobu, Kitagawa, Masashi, Fukayama |
| المصدر: | Cancer Science. 113:3608-3617 |
| بيانات النشر: | Wiley, 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Cancer Research, Oncology, Artificial Intelligence, Biopsy, Stomach, Humans, General Medicine |
| الوصف: | To overcome the increasing burden on pathologists in diagnosing gastric biopsies, we developed an artificial intelligence-based system for the pathological diagnosis of gastric biopsies (AI-G), which is expected to work well in daily clinical practice in multiple institutes. The multistage semantic segmentation for pathology (MSP) method utilizes the distribution of feature values extracted from patches of whole-slide images (WSI) like pathologists' "low-power view" information of microscopy. The training dataset included WSIs of 4511 gastric biopsy tissues from 984 patients. In tissue-level validation, MSP AI-G showed better accuracy (91.0%) than that of conventional patch-based AI-G (PB AI-G) (89.8%). Importantly, MSP AI-G unanimously achieved higher accuracy rates (0.946 ± 0.023) than PB AI-G (0.861 ± 0.078) in tissue-level analysis, when applied to the cohorts of 10 different institutes (3450 samples of 1772 patients in all institutes, 198-555 samples of 143-206 patients in each institute). MSP AI-G had high diagnostic accuracy and robustness in multi-institutions. When pathologists selectively review specimens in which pathologist's diagnosis and AI prediction are discordant, the requirement of a secondary review process is significantly less compared with reviewing all specimens by another pathologist. |
| تدمد: | 1349-7006 1347-9032 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6eb890ae809e54c66c10642733d3ea7 https://doi.org/10.1111/cas.15514 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....f6eb890ae809e54c66c10642733d3ea7 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 13497006 13479032 |
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