Optimizing Treatment Response Prediction in Locally Advanced Cervical Cancer Radiotherapy with Spatial and Task Attention Networks
Received Date: Oct 03, 2023 / Published Date: Oct 30, 2023
Abstract
Cervical cancer is a significant global health concern, and advancements in radiotherapy have played a crucial role in improving treatment outcomes. Locally advanced cervical cancer poses unique challenges due to the complex interplay of anatomical structures and varying tumor responses. Recent developments in medical imaging and artificial intelligence (AI) have paved the way for innovative approaches to treatment response prediction. One such promising avenue involves the integration of Spatial and Task Attention Networks.
Citation: Erten O (2023) Optimizing Treatment Response Prediction in LocallyAdvanced Cervical Cancer Radiotherapy with Spatial and Task Attention Networks.Current Trends Gynecol Oncol, 8: 180. Doi: 10.4172/ctgo.1000180
Copyright: © 2023 Erten Ö. This is an open-access article distributed under theterms of the Creative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided the original author andsource are credited.
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