Jinzheng Cai

Medicine · Health Sciences

23h-index2.0kcitations102works0.02yr avg
OpenAlex↗ORCID↗Google Scholar↗

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Research Topics

Radiomics and Machine Learning in Medical Imaging(80), Medical Imaging Techniques and Applications(51), Lung Cancer Diagnosis and Treatment(48), AI in cancer detection(22), Advanced Neural Network Applications(21)

Publications102 total

Figure S18 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S1 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S7 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S2 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S14 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Supplementary Protocol from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Supplementary Tables from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S1 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Supplementary Protocol from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S3 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S10 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S11 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S8 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S16 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S7 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S18 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S9 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S14 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Data from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
Figure S17 from Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging
2023Open Access
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Frequent Co-authors

Le Lü(36), Adam P. Harrison(26), Jing Xiao(25), Ke Yan(17), Youbao Tang(14), Lin Yang(13), Fuyong Xing(12), Dakai Jin(11), Xiaoshuang Shi(9), Alan Yuille(8), Zizhao Zhang(7), Yuanpu Xie(7), Lin Yang(7), Lingyun Huang(7), Pingjun Chen(6), Zhuotun Zhu(6), Yuankai Huo(6), Chi‐Tung Cheng(6), Fengze Liu(5), Ronald M. Summers(5)