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作 者:Zhenyu GONG Maximilian SCHWENDNER Tao XU
机构地区:[1]Department of Neurosurgery,Klinikum rechts der Isar,Technische Universität München,Ismaninger Str.22,81675 Munich,Germany [2]Department of Neurosurgery,Shanghai Changzheng Hospital,Naval Medical University,Shanghai 200003,China
出 处:《Clinical Cancer Bulletin》2022年第1期39-46,共8页临床癌症通报(英文)
基 金:the National Natural Science Foundation of China(No.81472354).
摘 要:As one of the tumors with substantial treatment difficulties,brain tumors have a high mortality rate and high treatment costs.Furthermore,surgical rection of deep-seated tumors or tumors involving eloquent areas is still a challenge for neurosurgeons.Therefore,accurate and early tumor diagnosis,selection of treatment options,and prediction of prognosis are important to improve patients’outcomes.Recently,with the rapid development of computational technology,the frequency of its application in clinical work has increased enormously and the acquisition of medical data has become more convenient and efficient.Furthermore,with the advancement of artificial intelligence(AI)—particularly,machine and deep learning—the applications of AI in medicine and especially neuro-oncology have enhanced diagnosis,treatment,and prognosis prediction of brain tumors topreviously unachievable levels.This article presents an overview of the applications of AI in neuro-oncology for diagnosis,prognosis,surgical treatment,and education.Furthermore,the advantages,perspectives,and challenges of AI for clinical applications in neuro-oncology are discussed.
关 键 词:artificial intelligence deep learning machine learning NEURO-ONCOLOGY
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