Optimize and Evaluate the Efficacy of Pairwise AE Model in Predicting the Prognosis of Concurrent Chemo-radiotherapy for Cervical Cancer
Miao Liu1, Qi Wang1, Gaofeng Shi1, Li Yang1, and Qinglei Shi2
1The Fourth Hospital of Hebei Medical University, Shi Jiazhuang, China, 2MR Scientific Marketing , Siemens Healthineers Ltd., Beijing, China
To overcome the small data set problems in clinical situations, this paper proposed a pairwise auto encoder (AE) model, which can learn more relationship information among samples to enhance the generalization ability, in predicting the prognosis of concurrent chemo-radiotherapy for LACC and demonstrated potential in this field.
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