Saima Rathore

800 total citations
27 papers, 559 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 559 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 and Signal Denoising Methods (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 and Signal Denoising Methods (4 papers). Saima Rathore collaborates with scholars based in Pakistan, United States and Canada. 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 544 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Saima Rathore Pakistan 15 269 247 210 86 60 27 559
Ayelet Akselrod-Ballin Israel 11 228 0.8× 181 0.7× 162 0.8× 40 0.5× 45 0.8× 20 516
Yunbo Guo China 9 322 1.2× 461 1.9× 394 1.9× 140 1.6× 30 0.5× 28 872
Shunxing Bao United States 14 472 1.8× 257 1.0× 359 1.7× 49 0.6× 76 1.3× 85 908
Michael Gadermayr Austria 11 149 0.6× 234 0.9× 159 0.8× 55 0.6× 37 0.6× 37 461
Ricardo J. Ferrari Brazil 14 238 0.9× 397 1.6× 388 1.8× 22 0.3× 132 2.2× 41 764
Zilong Hu China 11 203 0.8× 235 1.0× 134 0.6× 52 0.6× 103 1.7× 25 645
Changmiao Wang China 13 222 0.8× 178 0.7× 290 1.4× 35 0.4× 114 1.9× 69 797
John Arévalo Colombia 13 483 1.8× 705 2.9× 367 1.7× 121 1.4× 90 1.5× 30 1.0k
Jinzheng Cai United States 11 408 1.5× 383 1.6× 357 1.7× 72 0.8× 73 1.2× 17 773
Neslihan Bayramoğlu Finland 7 261 1.0× 343 1.4× 274 1.3× 48 0.6× 18 0.3× 17 551

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

20 of 20 papers shown
1.
Svaldi, Diana Otero, Saima Rathore, Leanne Munsie, et al.. (2024). Evaluation of Baseline Diffusion Tensor Imaging Biomarkers in phase 2 multi‐center PROSPECT‐ALZ study. Alzheimer s & Dementia. 20(S2).
2.
Rathore, Saima, Giulia Tronchin, Ixavier A. Higgins, et al.. (2023). Distinct associations between tau PET and cognitive impairment across brain regions and cognitive domains in Alzheimer’s disease. Alzheimer s & Dementia. 19(S14). 1 indexed citations
3.
4.
Steward, Anna, Davina Biel, Anna Dewenter, et al.. (2023). ApoE4 and Connectivity-Mediated Spreading of Tau Pathology at Lower Amyloid Levels. JAMA Neurology. 80(12). 1295–1295. 31 indexed citations
5.
Bathla, Girish, Yanan Liu, Neetu Soni, et al.. (2023). Differentiation Between Glioblastoma and Metastatic Disease on Conventional MRI Imaging Using 3D-Convolutional Neural Networks: Model Development and Validation. Academic Radiology. 31(5). 2041–2049. 5 indexed citations
6.
Chaddad, Ahmad, Michael Jonathan Kucharczyk, Abbas Cheddad, et al.. (2021). Magnetic Resonance Imaging Based Radiomic Models of Prostate Cancer: A Narrative Review. Cancers. 13(3). 552–552. 26 indexed citations
7.
Rathore, Saima, Ahmad Chaddad, Muhammad Aksam Iftikhar, Michel Bilello, & Ahmed Abdulkadir. (2021). Combining MRI and Histologic Imaging Features for Predicting Overall Survival in Patients with Glioma. Radiology Imaging Cancer. 3(4). e200108–e200108. 21 indexed citations
8.
Rathore, Saima, Tamim Niazi, Muhammad Aksam Iftikhar, & Ahmad Chaddad. (2020). Glioma Grading via Analysis of Digital Pathology Images Using Machine Learning. Cancers. 12(3). 578–578. 49 indexed citations
9.
Rathore, Saima, Tamim Niazi, Muhammad Aksam Iftikhar, et al.. (2020). Multimodal Ensemble-Based Segmentation of White Matter Lesions and Analysis of Their Differential Characteristics across Major Brain Regions. Applied Sciences. 10(6). 1903–1903. 4 indexed citations
10.
Chaddad, Ahmad, Michael Jonathan Kucharczyk, Christian Desrosiers, et al.. (2020). Deep Radiomic Analysis to Predict Gleason Score in Prostate Cancer. IEEE Access. 8. 167767–167778. 23 indexed citations
11.
Rathore, Saima, Muhammad Aksam Iftikhar, Ahmad Chaddad, et al.. (2019). Segmentation and Grade Prediction of Colon Cancer Digital Pathology Images Across Multiple Institutions. Cancers. 11(11). 1700–1700. 25 indexed citations
12.
Iftikhar, Muhammad Aksam, et al.. (2018). Object Size Measurement through Images: An Application to Measuring Human Foot Size. 298–302. 9 indexed citations
13.
Rathore, Saima, Mutawarra Hussain, Muhammad Aksam Iftikhar, & Abdul Jalil. (2015). Novel structural descriptors for automated colon cancer detection and grading. Computer Methods and Programs in Biomedicine. 121(2). 92–108. 33 indexed citations
14.
Ali, Ahmad, Abdul Jalil, Jianwei Niu, et al.. (2015). Visual object tracking—classical and contemporary approaches. Frontiers of Computer Science. 10(1). 167–188. 36 indexed citations
15.
Rathore, Saima, Muhammad Aksam Iftikhar, & Mutawarra Hussain. (2014). A novel approach for automatic gene selection and classification of gene based colon cancer datasets. 42–47. 11 indexed citations
16.
Rathore, Saima, Mutawarra Hussain, Muhammad Aksam Iftikhar, & Abdul Jalil. (2014). Ensemble classification of colon biopsy images based on information rich hybrid features. Computers in Biology and Medicine. 47. 76–92. 66 indexed citations
17.
Iftikhar, Muhammad Aksam, Abdul Jalil, Saima Rathore, & Mutawarra Hussain. (2014). Robust brain MRI denoising and segmentation using enhanced non‐local means algorithm. International Journal of Imaging Systems and Technology. 24(1). 52–66. 15 indexed citations
18.
Rathore, Saima, Mutawarra Hussain, Ahmad Ali, & Asifullah Khan. (2013). A Recent Survey on Colon Cancer Detection Techniques. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 10(3). 545–563. 87 indexed citations
19.
Rathore, Saima, et al.. (2013). Classification of colon biopsy images based on novel structural features. 1–6. 17 indexed citations
20.
Iftikhar, Muhammad Aksam, Saima Rathore, Abdul Jalil, & Mutawarra Hussain. (2013). A novel extension to non-local means algorithm: Application to brain MRI de-noising. 105. 195–200. 3 indexed citations

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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