Said Baidas

1.4k citations
22 papers · 443 · h-index 12

Impact in

  • Hematology top 10%
    • Multiple Myeloma Research and Treatments
    • Chronic Lymphocytic Leukemia Research
    • Estrogen and related hormone effects
    • Glioma Diagnosis and Treatment

Papers in

Said Baidas

21 papers receiving 433 citations

Peers

Said Baidas
Comparison fields: 5 of 62
  • Hematology 76
  • Genetics 68
  • Oncology 105
  • Pulmonary and Respiratory Medicine 98
  • Pathology and Forensic Medicine 49
Replace Merry Tetef with:
Merry Tetef United States
G Mathé France
Janet Fricker United Kingdom
Taher E. Taher United Kingdom
Fulvio Brema Italy
Valerie Relias United States
Sara Nunnery United States
Baohua Qian China
Ayako Mitsuma Japan
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Citations per field
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Citations per year

Countries citing papers authored by Said Baidas

Since Specialization
Citations

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

Fields of papers citing papers by Said Baidas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Said Baidas, 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 Said Baidas Line = papers co-authored together Said Baidas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003101
2 200094
3 199934
4 199428
5 201326
6 200224
7
Mantle cell lymphoma: clinicopathologic features and treatments.
200323
8 201722
9 200518
10 200313
11 200212
12 201212
13 201311
14 20097
15 20027
16
A case of concomitant T-cell large granular lymphocyte leukemia and plasma cell myeloma.
20114
17 20152
18
Phase I trial of irinotecan and epirubicin in advanced cancer. Preliminary report.
20022
19 20041
20 20201

About Said Baidas

Said Baidas is a scholar working on Oncology, Molecular Biology, Genetics, Pulmonary and Respiratory Medicine and Hematology, having authored 22 papers that have together received 443 indexed citations. Recurring topics across this work include Brain Metastases and Treatment (3 papers), Cancer Treatment and Pharmacology (2 papers), Chronic Myeloid Leukemia Treatments (2 papers), Cancer Risks and Factors (2 papers), Multiple Myeloma Research and Treatments (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Glioma Diagnosis and Treatment (2 papers) and Hemophilia Treatment and Research (1 paper). The work is most often cited by research in Hematology (76 citations), Genetics (68 citations), Oncology (105 citations), Pulmonary and Respiratory Medicine (98 citations) and Pathology and Forensic Medicine (49 citations). Said Baidas has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Pankaj Bhargava, Daniel F. Hayes, Eric P. Winer, Kevin M. McGrail, Anu Gupta, Herbert J. Manz, Michael D. Johnson, Michael Hawkins, C. Kent Osborne and Richard C. Yocum. Their work appears in journals such as Journal of Clinical Oncology, Cancer Biology & Therapy, Blood, Cancer Investigation and Expert Review of Anticancer Therapy.

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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