Jie Tian
Impact in
- Radiology, Nuclear Medicine and Imaging top 0.01%
- Radiomics and Machine Learning in Medical Imaging
- Optical Imaging and Spectroscopy Techniques
- Health Informatics top 0.1%
Papers in
-
- Photoacoustic and Ultrasonic Imaging 189
- Nanoplatforms for cancer theranostics 130
- Characterization and Applications of Magnetic Nanoparticles 73
-
- Optical Imaging and Spectroscopy Techniques 181
- Radiomics and Machine Learning in Medical Imaging 138
- Co-authors
- Di Dong (148 shared papers)Zhenyu Liu (106 shared papers)Wei Qin (92 shared papers)Kun Wang (106 shared papers)Zaiyi Liu (22 shared papers)Kai Yuan (58 shared papers)Jimin Liang (77 shared papers)Changhong Liang (9 shared papers)
- Journals
- European Radiology (31 papers)PLoS ONE (30 papers)European Journal of Nuclear Medicine and Molecular Imaging (23 papers)IEEE Transactions on Biomedical Engineering (22 papers)Physics in Medicine and Biology (21 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jie Tian
1.3k papers receiving 46.0k citations
Jie Tian's Hit Papers
Peers
Comparison fields: 5 of 219
- Radiology, Nuclear Medicine and Imaging 13.8k
- Health Informatics 486
- Biomedical Engineering 12.2k
- Hepatology 1.7k
- Biophysics 1.2k
Countries citing papers authored by Jie Tian
This map shows the geographic impact of Jie Tian's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jie Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jie Tian more than expected).
Fields of papers citing papers by Jie Tian
This network shows the impact of papers produced by Jie Tian. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jie Tian. The network helps show where Jie Tian may publish in the future.
Co-authors
The 25 scholars most cited alongside Jie Tian, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 1.3k papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer Hit paper breakdown → | 2016 | 1384 |
| 2 | First-in-human liver-tumour surgery guided by multispectral fluorescence imaging in the visible and near-infrared-I/II windows Hit paper breakdown → | 2019 | 911 |
| 3 | The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges Hit paper breakdown → | 2019 | 703 |
| 4 | Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non—Small Cell Lung Cancer Hit paper breakdown → | 2016 | 605 |
| 5 | DNA Origami as an In Vivo Drug Delivery Vehicle for Cancer Therapy Hit paper breakdown → | 2014 | 557 |
| 6 | Multi-crop Convolutional Neural Networks for lung nodule malignancy suspiciousness classification Hit paper breakdown → | 2016 | 512 |
| 7 | Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma Hit paper breakdown → | 2017 | 398 |
| 8 | Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study Hit paper breakdown → | 2018 | 395 |
| 9 | Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation Hit paper breakdown → | 2017 | 381 |
| 10 | 2018 | 358 | |
| 11 | Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning Hit paper breakdown → | 2019 | 333 |
| 12 | Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer Hit paper breakdown → | 2019 | 316 |
| 13 | Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study Hit paper breakdown → | 2020 | 306 |
| 14 | 2017 | 305 | |
| 15 | 2016 | 299 | |
| 16 | 2011 | 288 | |
| 17 | 2020 | 265 | |
| 18 | Prognostic Value of Deep Learning PET/CT-Based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma Hit paper breakdown → | 2019 | 253 |
| 19 | 2018 | 249 | |
| 20 | 2010 | 249 |
About Jie Tian
Jie Tian is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Pulmonary and Respiratory Medicine and Cognitive Neuroscience, having authored 1.3k papers that have together received 46.8k indexed citations. Recurring topics across this work include Photoacoustic and Ultrasonic Imaging (189 papers), Optical Imaging and Spectroscopy Techniques (181 papers), Radiomics and Machine Learning in Medical Imaging (138 papers), Nanoplatforms for cancer theranostics (130 papers), Characterization and Applications of Magnetic Nanoparticles (73 papers), Functional Brain Connectivity Studies (62 papers), Atmospheric chemistry and aerosols (59 papers) and Air Quality and Health Impacts (52 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (13.8k citations), Health Informatics (486 citations), Biomedical Engineering (12.2k citations), Hepatology (1.7k citations) and Biophysics (1.2k citations). Jie Tian has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Di Dong, Zhenyu Liu, Wei Qin, Kun Wang, Zaiyi Liu, Kai Yuan, Jimin Liang, Changhong Liang, Yang Du and Karen M. von Deneen. Their work appears in journals such as European Radiology, PLoS ONE, European Journal of Nuclear Medicine and Molecular Imaging, IEEE Transactions on Biomedical Engineering and Physics in Medicine and Biology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.