Debanjan Haldar

536 citations
22 papers · 250 indexed · h-index 9
Topics
Radiomics and Machine Learning in Medical Imaging (10 papers)Glioma Diagnosis and Treatment (5 papers)Traumatic Brain Injury and Neurovascular Disturbances (4 papers)

In The Last Decade

Debanjan Haldar

21 papers receiving 248 citations

Peers

Debanjan Haldar
Comparison fields: 5 of 59
  • Molecular Biology 68
  • Radiology, Nuclear Medicine and Imaging 66
  • Neurology 62
  • Genetics 54
  • Neurology 51
Replace Kevin Pierre with:
Kevin Pierre United States
Zhao Shi China
Roxana Améli France
Hung-Chieh Chen Taiwan
Johannes A. Vey Germany
Fariborz Faeghi Iran
Maria L. Gandía-González Spain
Domenique M. J. Müller Netherlands
Yutaka Katayama Japan
Amer Alaref Canada
Debanjan Haldar relative to Kevin Pierre United States Kevin Pierre's profile →
Citations per field
00.5×9.7×
Kevin Pierre · 1×
Citations per year

Countries citing papers authored by Debanjan Haldar

Since Specialization
Citations

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

Fields of papers citing papers by Debanjan Haldar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debanjan Haldar

This figure shows the co-authorship network connecting the top 25 collaborators of Debanjan Haldar. A scholar is included among the top collaborators of Debanjan Haldar 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 Debanjan Haldar. Debanjan Haldar 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
#WorkIndexed citations
1 11
2 1
3 1
4 1
5 0
6 1
7 25
8 21
9 20
10 1
11 9
12 2
13 1
14 9
15 5
16 2
17 5
18 4
19 72
20 38

About Debanjan Haldar

Debanjan Haldar is a scholar working on Geriatrics and Gerontology, Radiology, Nuclear Medicine and Imaging and Genetics, having authored 22 papers that have together received 250 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Glioma Diagnosis and Treatment (5 papers) and Traumatic Brain Injury and Neurovascular Disturbances (4 papers). The work is most often cited by research in Health Informatics (9 citations), Neurology (51 citations) and Genetics (54 citations). Debanjan Haldar has collaborated with scholars based in United States, France and Norway. Frequent co-authors include P. M. Abdul‐Muneer, Ram Kuwar, Adam Resnick, Ali Nabavizadeh, Phillip B. Storm, Anahita Fathi Kazerooni, Ariana Familiar, Nastaran Khalili, Bryan J. Pfister and Vijayalakshmi Santhakumar. Their work appears in journals such as Journal of neurosurgery, Neurosurgery and Brain Behavior and Immunity.

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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