- 专利标题: Training artificial intelligence models for radiation therapy
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申请号: US17124249申请日: 2020-12-16
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公开(公告)号: US11612761B2公开(公告)日: 2023-03-28
- 发明人: Shahab Basiri , Mikko Hakala , Esa Kuusela , Elena Czeizler
- 申请人: VARIAN MEDICAL SYSTEMS INTERNATIONAL AG
- 申请人地址: US CA Palo Alto
- 专利权人: VARIAN MEDICAL SYSTEMS INTERNATIONAL AG
- 当前专利权人: VARIAN MEDICAL SYSTEMS INTERNATIONAL AG
- 当前专利权人地址: US CA Palo Alto
- 代理机构: Foley & Lardner LLP
- 主分类号: A61N5/10
- IPC分类号: A61N5/10 ; G06N3/08
摘要:
Disclosed herein are systems and methods for iteratively training artificial intelligence models using reinforcement learning techniques. With each iteration, a training agent applies a random radiation therapy treatment attribute corresponding to the radiation therapy treatment attribute associated with previously performed radiation therapy treatments when an epsilon value indicative of a likelihood of exploration and exploitation training of the artificial intelligence model satisfies a threshold. When the epsilon value does not satisfy the threshold, the agent generates, using an existing policy, a first predicted radiation therapy treatment attribute, and generates, using a predefined model, a second predicted radiation therapy treatment attribute. The agent applies one of the first predicted radiation therapy treatment attribute or the second predicted radiation therapy treatment attribute that is associated with a higher reward. The agent iteratively repeats training the artificial intelligence model until the existing policy satisfies an accuracy threshold.
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