Jiacheng Song
- Radiology, Nuclear Medicine and Imaging top 5%
- Obstetrics and Gynecology top 5%
- Biomedical Engineering
- Molecular Biology
- Oncology
- Co-authors
- Ting ChenQiming HuAining ZhangHai‐Bin ShiJing YuDongya HuangZhanlong MaQiang Yu
- Topics
- MRI in cancer diagnosis (15 papers)Radiomics and Machine Learning in Medical Imaging (13 papers)Endometrial and Cervical Cancer Treatments (13 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaPLoS ONE
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Jiacheng Song
44 papers receiving 490 citations
Peers
Comparison fields: 5 of 75
- Radiology, Nuclear Medicine and Imaging 247
- Obstetrics and Gynecology 126
- Biomedical Engineering 81
- Molecular Biology 77
- Oncology 65
Countries citing papers authored by Jiacheng Song
This map shows the geographic impact of Jiacheng Song'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 Jiacheng Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiacheng Song more than expected).
Fields of papers citing papers by Jiacheng Song
This network shows the impact of papers produced by Jiacheng Song. 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 Jiacheng Song. The network helps show where Jiacheng Song may publish in the future.
Co-authorship network of co-authors of Jiacheng Song
This figure shows the co-authorship network connecting the top 25 collaborators of Jiacheng Song. A scholar is included among the top collaborators of Jiacheng Song based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jiacheng Song. Jiacheng Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 7 | |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 3 | |
| 11 | 3 | |
| 12 | 5 | |
| 13 | 29 | |
| 14 | Nomogram Predicting Overall Survival of Resected Locally Advanced Rectal Cancer Patients with Neoadjuvant Chemoradiotherapy | 1 |
| 15 | 28 | |
| 16 | 11 | |
| 17 | 8 | |
| 18 | 54 | |
| 19 | 7 | |
| 20 | 7 |
About Jiacheng Song
Jiacheng Song is a scholar working on Obstetrics and Gynecology, Reproductive Medicine and Radiology, Nuclear Medicine and Imaging, having authored 49 papers that have together received 498 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Endometrial and Cervical Cancer Treatments (13 papers). The work is most often cited by research in Obstetrics and Gynecology (126 citations), Radiology, Nuclear Medicine and Imaging (247 citations) and Modeling and Simulation (42 citations). Jiacheng Song has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ting Chen, Qiming Hu, Aining Zhang, Hai‐Bin Shi, Jing Yu, Dongya Huang, Zhanlong Ma, Qiang Yu, Junwen Huang and Ian Turner. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.
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.