Nazik Alturki
- Artificial Intelligence top 2%
- Computer Science Applications top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Health Informatics top 1%
- Co-authors
- Mohammad Amin KuhailOumaima SaidaniAntonio LiottaNajah AlsubaieHanan AljuaidLucia CavallaroZuhaira Muhammad ZainLeila Jamel
- Topics
- IoT and Edge/Fog Computing (6 papers)Artificial Intelligence in Healthcare (6 papers)Brain Tumor Detection and Classification (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Access
- Partner nations
- Saudi ArabiaPakistanSouth Korea
In The Last Decade
Nazik Alturki
37 papers receiving 995 citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Artificial Intelligence 594
- Computer Science Applications 214
- Radiology, Nuclear Medicine and Imaging 201
- Computer Vision and Pattern Recognition 135
- Health Informatics 118
Countries citing papers authored by Nazik Alturki
This map shows the geographic impact of Nazik Alturki'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 Nazik Alturki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nazik Alturki more than expected).
Fields of papers citing papers by Nazik Alturki
This network shows the impact of papers produced by Nazik Alturki. 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 Nazik Alturki. The network helps show where Nazik Alturki may publish in the future.
Co-authorship network of co-authors of Nazik Alturki
This figure shows the co-authorship network connecting the top 25 collaborators of Nazik Alturki. A scholar is included among the top collaborators of Nazik Alturki 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 Nazik Alturki. Nazik Alturki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 5 | |
| 9 | 0 | |
| 10 | 3 | |
| 11 | 21 | |
| 12 | 27 | |
| 13 | 28 | |
| 14 | 3 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 27 | |
| 18 | Interacting with educational chatbots: A systematic reviewbreakdown → | 379 |
| 19 | 13 | |
| 20 | 42 |
About Nazik Alturki
Nazik Alturki is a scholar working on Health Information Management, Neurology and Computer Vision and Pattern Recognition, having authored 50 papers that have together received 1.1k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (6 papers), Artificial Intelligence in Healthcare (6 papers) and Brain Tumor Detection and Classification (6 papers). The work is most often cited by research in Health Informatics (118 citations), Computer Science Applications (214 citations) and Artificial Intelligence (594 citations). Nazik Alturki has collaborated with scholars based in Saudi Arabia, Pakistan and South Korea. Frequent co-authors include Mohammad Amin Kuhail, Oumaima Saidani, Antonio Liotta, Najah Alsubaie, Hanan Aljuaid, Lucia Cavallaro, Zuhaira Muhammad Zain, Leila Jamel, Muhammad Umer and Imran Ashraf. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.
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.