Saba Shafi
- Oncology
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Molecular Biology
- Pulmonary and Respiratory Medicine
- Co-authors
- Anil V. ParwaniDavid L. RimmThazin Nwe AungMyrto MoutafiZaibo LiAileen I. FernandezNiki GavrielatouSandra Martínez-Morilla
- Topics
- Cancer Immunotherapy and Biomarkers (14 papers)Immunotherapy and Immune Responses (8 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)
- Partner nations
- United StatesGreeceIndia
In The Last Decade
Saba Shafi
40 papers receiving 370 citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Oncology 135
- Radiology, Nuclear Medicine and Imaging 126
- Artificial Intelligence 123
- Molecular Biology 60
- Pulmonary and Respiratory Medicine 50
Countries citing papers authored by Saba Shafi
This map shows the geographic impact of Saba Shafi'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 Saba Shafi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saba Shafi more than expected).
Fields of papers citing papers by Saba Shafi
This network shows the impact of papers produced by Saba Shafi. 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 Saba Shafi. The network helps show where Saba Shafi may publish in the future.
Co-authorship network of co-authors of Saba Shafi
This figure shows the co-authorship network connecting the top 25 collaborators of Saba Shafi. A scholar is included among the top collaborators of Saba Shafi 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 Saba Shafi. Saba Shafi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 26 | |
| 4 | 2 | |
| 5 | 10 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | Artificial intelligence in diagnostic pathologybreakdown → | 128 |
| 10 | 6 | |
| 11 | 2 | |
| 12 | 12 | |
| 13 | 8 | |
| 14 | 5 | |
| 15 | 18 | |
| 16 | 2 | |
| 17 | 25 | |
| 18 | 0 | |
| 19 | 6 | |
| 20 | Hormone replacement therapy menopause with a better future--a survey of views on hormone replacement therapy (HRT). | 5 |
About Saba Shafi
Saba Shafi is a scholar working on Oncology, Pathology and Forensic Medicine and Immunology, having authored 42 papers that have together received 387 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (14 papers), Immunotherapy and Immune Responses (8 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Health Informatics (50 citations), Radiology, Nuclear Medicine and Imaging (126 citations) and Oncology (135 citations). Saba Shafi has collaborated with scholars based in United States, Greece and India. Frequent co-authors include Anil V. Parwani, David L. Rimm, Thazin Nwe Aung, Myrto Moutafi, Zaibo Li, Aileen I. Fernandez, Niki Gavrielatou, Sandra Martínez-Morilla, Yalai Bai and Vesal Yaghoobi. Their work appears in journals such as Journal of Clinical Oncology, The American Journal of Surgical Pathology and Human Pathology.
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.