Fade Mahmoud

2.1k citations
51 papers · 1.5k · h-index 20

Impact in

  • Oncology top 5%
    • Cancer Immunotherapy and Biomarkers
    • Inflammatory Biomarkers in Disease Prognosis
    • CAR-T cell therapy research
  • Physiology top 10%
    • Nutrition and Health in Aging
    • Body Composition Measurement Techniques

Papers in

    • Cancer Immunotherapy and Biomarkers 14
    • CAR-T cell therapy research 5
    • Lung Cancer Research Studies 3
    • Cancer Treatment and Pharmacology 2
    • Melanoma and MAPK Pathways 6

Fade Mahmoud

48 papers receiving 1.5k citations

Peers

Fade Mahmoud
Comparison fields: 5 of 111
  • Oncology 701
  • Physiology 306
  • Immunology 226
  • Geriatrics and Gerontology 38
  • Cancer Research 123
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Fade Mahmoud relative to Sanjeev Kumar United States Sanjeev Kumar's profile →
Citations per field
00.5×3.4×
Sanjeev Kumar · 1×
Citations per year

Countries citing papers authored by Fade Mahmoud

Since Specialization
Citations

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

Fields of papers citing papers by Fade Mahmoud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Fade Mahmoud, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fade Mahmoud Line = papers co-authored together Fade Mahmoud links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002253
2 2018191
3 2003126
4 2003119
5 201672
6 200366
7 201760
8 200356
9 201144
10 201942
11 201739
12 201638
13 202137
14 201537
15 200737
16 201830
17 201127
18 201725
19 201624
20 201622

About Fade Mahmoud

Fade Mahmoud is a scholar working on Oncology, Molecular Biology, Immunology, Epidemiology and Pulmonary and Respiratory Medicine, having authored 51 papers that have together received 1.5k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (14 papers), Melanoma and MAPK Pathways (6 papers), Immunotherapy and Immune Responses (6 papers), CAR-T cell therapy research (5 papers), Pain Management and Opioid Use (3 papers), Lung Cancer Research Studies (3 papers), Nutrition and Health in Aging (3 papers) and Cancer Treatment and Pharmacology (2 papers). The work is most often cited by research in Oncology (701 citations), Physiology (306 citations), Immunology (226 citations), Geriatrics and Gerontology (38 citations) and Cancer Research (123 citations). Fade Mahmoud has collaborated with scholars based in United States, United Kingdom and Egypt. Frequent co-authors include Nilo Rivera, Declan Walsh, Kristine A. Nelson, Laura F. Hutchins, Nabeel Sarhill, Jiaxin Niu, Rahul Ravilla, Madappa N. Kundranda, Mellar P. Davis and Tomislav Dragovich. Their work appears in journals such as Journal of Clinical Oncology, Supportive Care in Cancer, Current Oncology Reports, Cancer Biology & Therapy and Palliative Medicine.

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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