Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Yuchen Qiu

Showing results (51-60 of 75) with videos related to

Pageof 8
Sort By:
Frontiers in Radiology|April 2, 2026
A vision transformer-radiomics approach for enhanced chemotherapy outcome prediction in ovarian cancerNeman Abdoli, Patrik Gilley, Ke Zhang, et al.
Bioengineering (Basel, Switzerland)|November 25, 2023
Evaluating the Effectiveness of 2D and 3D CT Image Features for Predicting Tumor Response to ChemotherapyNeman Abdoli, Ke Zhang, Patrik Gilley, et al.
IEEE Transactions on Medical Imaging|September 4, 2015
A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image RegistrationMaxine Tan, Zheng Li, Yuchen Qiu, et al.
Academic Radiology|May 31, 2017
Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to ChemotherapyGopichandh Danala, Theresa Thai, Camille C Gunderson, et al.
Annals of Biomedical Engineering|July 28, 2018
Classification of Tumor Epithelium and Stroma by Exploiting Image Features Learned by Deep Convolutional Neural NetworksYue Du, Roy Zhang, Abolfazl Zargari, et al.
Arxiv|September 25, 2023
Developing a Novel Image Marker to Predict the Clinical Outcome of Neoadjuvant Chemotherapy (NACT) for Ovarian Cancer PatientsKe Zhang, Neman Abdoli, Patrik Gilley, et al.
Nature Communications|September 4, 2019
Nano-confined crystallization of organic ultrathin nanostructure arrays with programmable geometriesHanfei Gao, Yuchen Qiu, Jiangang Feng, et al.
BMC Medical Imaging|December 16, 2025
Parameter efficient fine-tunning of foundation model to facilitate tumor response prediction for ovarian cancer patientsKe Zhang, Patrik Gilley, Neman Abdoli, et al.
Computers in Biology and Medicine|March 9, 2024
Developing a novel image marker to predict the clinical outcome of neoadjuvant chemotherapy (NACT) for ovarian cancer patientsKe Zhang, Neman Abdoli, Patrik Gilley, et al.
Medical Image Analysis|April 26, 2022
Recent advances and clinical applications of deep learning in medical image analysisXuxin Chen, Ximin Wang, Ke Zhang, et al.
Pageof 8

Showing results (51-60 of 75) with videos related to

Sort By:
Pageof 8
Frontiers in Radiology|April 2, 2026
A vision transformer-radiomics approach for enhanced chemotherapy outcome prediction in ovarian cancerNeman Abdoli, Patrik Gilley, Ke Zhang, et al.
Bioengineering (Basel, Switzerland)|November 25, 2023
Evaluating the Effectiveness of 2D and 3D CT Image Features for Predicting Tumor Response to ChemotherapyNeman Abdoli, Ke Zhang, Patrik Gilley, et al.
IEEE Transactions on Medical Imaging|September 4, 2015
A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image RegistrationMaxine Tan, Zheng Li, Yuchen Qiu, et al.
Academic Radiology|May 31, 2017
Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to ChemotherapyGopichandh Danala, Theresa Thai, Camille C Gunderson, et al.
Annals of Biomedical Engineering|July 28, 2018
Classification of Tumor Epithelium and Stroma by Exploiting Image Features Learned by Deep Convolutional Neural NetworksYue Du, Roy Zhang, Abolfazl Zargari, et al.
Arxiv|September 25, 2023
Developing a Novel Image Marker to Predict the Clinical Outcome of Neoadjuvant Chemotherapy (NACT) for Ovarian Cancer PatientsKe Zhang, Neman Abdoli, Patrik Gilley, et al.
Nature Communications|September 4, 2019
Nano-confined crystallization of organic ultrathin nanostructure arrays with programmable geometriesHanfei Gao, Yuchen Qiu, Jiangang Feng, et al.
BMC Medical Imaging|December 16, 2025
Parameter efficient fine-tunning of foundation model to facilitate tumor response prediction for ovarian cancer patientsKe Zhang, Patrik Gilley, Neman Abdoli, et al.
Computers in Biology and Medicine|March 9, 2024
Developing a novel image marker to predict the clinical outcome of neoadjuvant chemotherapy (NACT) for ovarian cancer patientsKe Zhang, Neman Abdoli, Patrik Gilley, et al.
Medical Image Analysis|April 26, 2022
Recent advances and clinical applications of deep learning in medical image analysisXuxin Chen, Ximin Wang, Ke Zhang, et al.
Pageof 8