Haixia Long
- Artificial Intelligence
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition
- Health Information Management top 5%
- Topics
- Machine Learning in Bioinformatics (5 papers)Brain Tumor Detection and Classification (4 papers)Genomics and Phylogenetic Studies (4 papers)
- Cited by
- Health Information ManagementRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Journals
- Scientific ReportsIEEE AccessSensors
- Partner nations
- ChinaPakistanSaudi Arabia
In The Last Decade
Haixia Long
24 papers receiving 247 citations
Hit Papers
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 74
- Molecular Biology 71
- Radiology, Nuclear Medicine and Imaging 66
- Computer Vision and Pattern Recognition 49
- Health Information Management 32
Countries citing papers authored by Haixia Long
This map shows the geographic impact of Haixia Long'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 Haixia Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haixia Long more than expected).
Fields of papers citing papers by Haixia Long
This network shows the impact of papers produced by Haixia Long. 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 Haixia Long. The network helps show where Haixia Long may publish in the future.
Co-authorship network of co-authors of Haixia Long
This figure shows the co-authorship network connecting the top 25 collaborators of Haixia Long. A scholar is included among the top collaborators of Haixia Long 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 Haixia Long. Haixia Long is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Quantum computational infusion in extreme learning machines for early multi-cancer detectionbreakdown → | 18 |
| 2 | 14 | |
| 3 | 5 | |
| 4 | 4 | |
| 5 | NIMEQ-SACNet: A novel self-attention precision medicine model for vision-threatening diabetic retinopathy using image databreakdown → | 53 |
| 6 | 31 | |
| 7 | 11 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 6 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 15 | |
| 14 | 19 | |
| 15 | 8 | |
| 16 | 7 | |
| 17 | 8 | |
| 18 | 27 | |
| 19 | 7 | |
| 20 | 2 |
About Haixia Long
Haixia Long is a scholar working on Biophysics, Health Information Management and Neurology, having authored 24 papers that have together received 260 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (5 papers), Brain Tumor Detection and Classification (4 papers) and Genomics and Phylogenetic Studies (4 papers). The work is most often cited by research in Health Information Management (32 citations), Radiology, Nuclear Medicine and Imaging (66 citations) and Computer Vision and Pattern Recognition (49 citations). Haixia Long has collaborated with scholars based in China, Pakistan and Saudi Arabia. Frequent co-authors include Anas Bilal, Muhammad Shafiq, Xiaowen Liu, Manzhi Li, Jia Huang, Azhar Imran, Ming Lin, Hai Fu, Haiyan Fu and Ahmed M. El‐Sherbeeny. Their work appears in journals such as Scientific Reports, 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.