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人工智能在癌症中的未来
FastGlioma检测并计算剩余肿瘤的平均准确率约为92%。
在FastGlioma预测或图像和荧光引导方法指导下的手术比较中,人工智能技术仅错过了3.8%的高风险残留肿瘤,而传统方法的失误率接近25%。
https://www.ebiotrade.com/newsf/2024-11/20241114020242153.htm
http://www.pubmedplus.cn/P/SearchQuickResult?wd=26bd7d3d-7080-4e1e-b6e8-b6b74405565b
01. | Deep Learning | 112 篇 | 100.000% |
02. | Humans | 107 篇 | 95.536% |
03. | Artificial Intelligence | 70 篇 | 62.500% |
04. | Algorithms | 29 篇 | 25.893% |
05. | Machine Learning | 25 篇 | 22.321% |
06. | Neural Networks, Computer | 22 篇 | 19.643% |
07. | Female | 21 篇 | 18.750% |
08. | Image Processing, Computer-Assisted | 16 篇 | 14.286% |
09. | Male | 15 篇 | 13.393% |
10. | Neoplasms | 15 篇 | 13.393% |
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