<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zuo, Chenyu</style></author><author><style face="normal" font="default" size="100%">Lei, Runhong</style></author><author><style face="normal" font="default" size="100%">Xi Liu</style></author><author><style face="normal" font="default" size="100%">Niu, Kai</style></author><author><style face="normal" font="default" size="100%">He, Zhiqiang</style></author><author><style face="normal" font="default" size="100%">Yang, Ruijie</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automatic Segmentation of Organs-At-Risk and Clinical Target Volume for Cervical Cancer Using Manifold Learning</style></title><secondary-title><style face="normal" font="default" size="100%">2024 International Joint Conference on Neural Networks (IJCNN)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2024</style></year></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pages><style face="normal" font="default" size="100%">1-7</style></pages><isbn><style face="normal" font="default" size="100%">9798350359312</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>