Applications of artificial intelligence in neuro-oncology

被引：31
|
作者：
Aneja, Sanjay [1 ,2 ,3 ]
Chang, Enoch [3 ]
Omuro, Antonio [1 ,2 ]
机构：
[1] Yale Canc Ctr, Yale Brain Tumor Ctr, New Haven, CT USA
[2] Smilow Canc Hosp, New Haven, CT USA
[3] Yale Dept Therapeut Radiol, 330 Cedar St,Clin Bldg 326, New Haven, CT 06520 USA
来源：
CURRENT OPINION IN NEUROLOGY | 2019年 / 32卷 / 06期
关键词：
artificial intelligence; deep learning; machine learning; neuro-oncology; CONVOLUTIONAL NEURAL-NETWORK; CENTRAL-NERVOUS-SYSTEM; BRAIN METASTASES; GRADE GLIOMAS; MR-IMAGES; CLASSIFICATION; SEGMENTATION; PROGRESSION;
D O I：
10.1097/WCO.0000000000000761
中图分类号：
R74 [神经病学与精神病学];
学科分类号：
摘要：
Purpose of review To discuss recent applications of artificial intelligence within the field of neuro-oncology and highlight emerging challenges in integrating artificial intelligence within clinical practice. Recent findings In the field of image analysis, artificial intelligence has shown promise in aiding clinicians with incorporating an increasing amount of data in genomics, detection, diagnosis, classification, risk stratification, prognosis, and treatment response. Artificial intelligence has also been applied in epigenetics, pathology, and natural language processing. Summary Although nascent, applications of artificial intelligence within neuro-oncology show significant promise. Artificial intelligence algorithms will likely improve our understanding of brain tumors and help drive future innovations in neuro-oncology.
引用
收藏
页码：850 / 856
页数：7
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