Saima Rathore

38 total papers · 788 total citations
27 papers, 550 citations indexed

About

Saima Rathore is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Saima Rathore has authored 27 papers receiving a total of 550 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 12 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Artificial Intelligence. Recurrent topics in Saima Rathore's work include Radiomics and Machine Learning in Medical Imaging (10 papers), AI in cancer detection (9 papers) and Image Retrieval and Classification Techniques (4 papers). Saima Rathore is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (10 papers), AI in cancer detection (9 papers) and Image Retrieval and Classification Techniques (4 papers). Saima Rathore collaborates with scholars based in Pakistan, United States and China. Saima Rathore's co-authors include Muhammad Aksam Iftikhar, Mutawarra Hussain, Abdul Jalil, Ahmad Chaddad, Ahmad Ali, Tamim Niazi, Asifullah Khan, Michel Bilello, Christian Desrosiers and Mingli Zhang and has published in prestigious journals such as IEEE Access, Neurocomputing and JAMA Neurology.

In The Last Decade

Saima Rathore

26 papers receiving 536 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Saima Rathore	267	244	209	86	60	27	550
Ayelet Akselrod-Ballin	228 0.9×	181 0.7×	162 0.8×	40 0.5×	71 1.2×	20	514
Zhenyuan Ning	338 1.3×	269 1.1×	120 0.6×	43 0.5×	99 1.6×	25	541
Spiros Kostopoulos	307 1.1×	249 1.0×	127 0.6×	60 0.7×	54 0.9×	66	613
Antonio Foncubierta–Rodríguez	236 0.9×	164 0.7×	187 0.9×	39 0.5×	22 0.4×	30	534
Wei Yang	283 1.1×	397 1.6×	177 0.8×	75 0.9×	26 0.4×	17	536
Żaneta Świderska-Chadaj	270 1.0×	359 1.5×	148 0.7×	100 1.2×	13 0.2×	31	583
Pingjun Chen	236 0.9×	277 1.1×	170 0.8×	52 0.6×	13 0.2×	22	614
Michael Gadermayr	149 0.6×	231 0.9×	156 0.7×	54 0.6×	13 0.2×	36	452
Neslihan Bayramoğlu	261 1.0×	342 1.4×	274 1.3×	48 0.6×	52 0.9×	17	550
Abdul Majid	175 0.7×	218 0.9×	142 0.7×	61 0.7×	36 0.6×	40	599

Countries citing papers authored by Saima Rathore

Since Specialization

Citations

This map shows the geographic impact of Saima Rathore'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 Saima Rathore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saima Rathore more than expected).

Fields of papers citing papers by Saima Rathore

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Saima Rathore. 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 Saima Rathore. The network helps show where Saima Rathore may publish in the future.

Co-authorship network of co-authors of Saima Rathore

This figure shows the co-authorship network connecting the top 25 collaborators of Saima Rathore. A scholar is included among the top collaborators of Saima Rathore 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 Saima Rathore. Saima Rathore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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