Suhas Singla

439 citations
36 papers · 331 · h-index 11

Impact in

Papers in

Suhas Singla

33 papers receiving 321 citations

Peers

Suhas Singla
Comparison fields: 5 of 51
  • Radiology, Nuclear Medicine and Imaging 159
  • Microbiology 5
  • Oncology 80
  • Epidemiology 93
  • Genetics 28
Replace Giulia Santo with:
Giulia Santo Italy
Jirka Grosse Germany
Alessandra Musto Italy
S. Ayakawa Japan
Priyanka Verma India
C. Hashizume Japan
Osama Al‐Saif Saudi Arabia
Alaa Kandil Egypt
F Cameron Australia
Ryan Neff United States
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Citations per field
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Citations per year

Countries citing papers authored by Suhas Singla

Since Specialization
Citations

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

Fields of papers citing papers by Suhas Singla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201465
2 201341
3 201241
4
An approach for conjugation of (177) Lu- DOTA-SCN- Rituximab (BioSim) & its evaluation for radioimmunotherapy of relapsed & refractory B-cell non Hodgkins lymphoma patients.
201419
5 201318
6 201417
7 201312
8 201211
9 201611
10 201311
11
An approach for conjugation of 177 Lu- DOTA-SCN- Rituximab (BioSim) & its evaluation for radioimmunotherapy of relapsed & refractory B-cell non Hodgkins lymphoma patients
201410
12 20128
13 20178
14 20168
15 20166
16 20145
17 20124
18 20134
19 20123
20 20143

About Suhas Singla

Suhas Singla is a scholar working on Epidemiology, Pathology and Forensic Medicine, Surgery, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 36 papers that have together received 331 indexed citations. Recurring topics across this work include Neuroendocrine Tumor Research Advances (7 papers), Radiopharmaceutical Chemistry and Applications (5 papers), Medical Imaging and Pathology Studies (4 papers), Breast Lesions and Carcinomas (4 papers), Liver Disease Diagnosis and Treatment (3 papers), Neuroblastoma Research and Treatments (3 papers), Liver Disease and Transplantation (3 papers) and Lymphoma Diagnosis and Treatment (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (159 citations), Microbiology (5 citations), Oncology (80 citations), Epidemiology (93 citations) and Genetics (28 citations). Suhas Singla has collaborated with scholars based in India and United States. Frequent co-authors include Chandrasekhar Bal, Santosh Kumar Gupta, Krishan Kant Agarwal, Parul Thakral, Geetanjali Arora, Punit Sharma, Sellam Karunanithi, Madhav Prasad Yadav, Chandrasekhar Bal and Arun Malhotra. Their work appears in journals such as Nuclear Medicine Communications, Clinical Nuclear Medicine, Renal Failure, Cancer Biotherapy and Radiopharmaceuticals and Annals of Oncology.

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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