Song Guo
- Radiology, Nuclear Medicine and Imaging top 2%
- Computer Vision and Pattern Recognition top 2%
- Ophthalmology top 1%
- Artificial Intelligence top 10%
- Health Information Management top 2%
- Co-authors
- Kai WangTao LiHong KangYingqi GaoHanruo LiuYujun ZhangNing LiDacheng Tao
- Topics
- Retinal Imaging and Analysis (16 papers)Digital Imaging for Blood Diseases (7 papers)Retinal Diseases and Treatments (6 papers)
- Cited by
- OphthalmologyRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessSensors
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Song Guo
48 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Radiology, Nuclear Medicine and Imaging 660
- Computer Vision and Pattern Recognition 465
- Ophthalmology 445
- Artificial Intelligence 92
- Health Information Management 86
Countries citing papers authored by Song Guo
This map shows the geographic impact of Song Guo'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 Song Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Guo more than expected).
Fields of papers citing papers by Song Guo
This network shows the impact of papers produced by Song Guo. 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 Song Guo. The network helps show where Song Guo may publish in the future.
Co-authorship network of co-authors of Song Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Song Guo. A scholar is included among the top collaborators of Song Guo 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 Song Guo. Song Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 14 | |
| 9 | 8 | |
| 10 | 1 | |
| 11 | 25 | |
| 12 | 24 | |
| 13 | Diagnostic assessment of deep learning algorithms for diabetic retinopathy screeningbreakdown → | 355 |
| 14 | 98 | |
| 15 | 34 | |
| 16 | 130 | |
| 17 | 3 | |
| 18 | 2 | |
| 19 | 30 | |
| 20 | The Pre-Processing of Multiwavelet and Its Application in Image Compression | 0 |
About Song Guo
Song Guo is a scholar working on Ophthalmology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 53 papers that have together received 1.1k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (16 papers), Digital Imaging for Blood Diseases (7 papers) and Retinal Diseases and Treatments (6 papers). The work is most often cited by research in Ophthalmology (445 citations), Radiology, Nuclear Medicine and Imaging (660 citations) and Computer Vision and Pattern Recognition (465 citations). Song Guo has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Kai Wang, Tao Li, Hong Kang, Yingqi Gao, Hanruo Liu, Yujun Zhang, Ning Li, Dacheng Tao, Xinchao Wang and Jingya Wang. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.
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.