2026-10-14T23:42:03Z https://www.scidb.cn/oai

10.57760/sciencedb.xbyxb.00196 2026-07-28T14:37:21Z

2026-07-28 Artificial intelligence enables the mechanism of whole-cycle precision diagnosis and treatment of gastrointestinal stromal tumor doi:10.57760/sciencedb.xbyxb.00196 en This figure system shows the innovative model of "artificial intelligence + organoids" to enable the whole-cycle precise diagnosis and treatment of gastrointestinal stromal tumor (GIST). The left side summarizes six core problems in the current clinical diagnosis and treatment of GIST, including resistance to targeted drugs, insufficient accuracy of risk stratification, difficulty in non-invasive prediction of gene mutations, limitation of imaging discrimination, immature organoid technology, and multimodal data siloes. On the right side, an AI-driven "prevention, diagnosis, treatment, and follow-up" whole-process solution was constructed, covering the key links of non-invasive imaging risk stratification based on deep learning, fusion diagnosis of radiomics and pathology, intelligent drug susceptibility screening of organoids, clinical decision support system (CDSS), dynamic efficacy monitoring, drug resistance warning, and early recurrence identification. At the end of the figure, it is summarized that AI can promote the evolution of GIST diagnosis and treatment to the direction of precision, intelligence and closed-loop management through the three technical paths of non-invasive imaging risk stratification, multimodal data fusion and organoid intelligent analysis. gastrointestinal stromal tumor; artificial intelligence; organoids; drug sensitivity testing; virtual screening; multimodal data fusion You Junzhao Tang Hongtao Jiang Shun Quan Zhengchao Zhang Yimou Hou Nengyi Zhou Chuan Pang Minghui PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank