Anupam Ghosh

1.7k citations
107 papers · 972 indexed · h-index 18
Topics
Gene expression and cancer classification (25 papers)Bioinformatics and Genomic Networks (21 papers)Machine Learning in Bioinformatics (17 papers)
Journals
The LancetSHILAP Revista de lepidopterologíaBlood
Partner nations
IndiaHong KongChina

In The Last Decade

Anupam Ghosh

96 papers receiving 907 citations

Peers

Anupam Ghosh
Comparison fields: 5 of 129
  • Pediatrics, Perinatology and Child Health 269
  • Genetics 175
  • Artificial Intelligence 143
  • Hematology 142
  • Obstetrics and Gynecology 135
Replace Ashish Verma with:
Ashish Verma India
Hayoung Oh South Korea
Huaizhong Hu United States
Faisal Azam Saudi Arabia
Pegah Khosravi United States
Ángel Molina Spain
Katsumi Murakami Japan
Donglin Zeng United States
Nicolas Jay France
Nicolas Garcelon France
Anupam Ghosh relative to Ashish Verma India Ashish Verma's profile →
Citations per field
00.5×10×12.9×
Ashish Verma · 1×
Citations per year

Countries citing papers authored by Anupam Ghosh

Since Specialization
Citations

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

Fields of papers citing papers by Anupam Ghosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anupam Ghosh

This figure shows the co-authorship network connecting the top 25 collaborators of Anupam Ghosh. A scholar is included among the top collaborators of Anupam Ghosh 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 Anupam Ghosh. Anupam Ghosh 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 0
2 2
3 5
4 3
5 6
6 0
7 19
8 7
9
IndoWordNet Dictionary: An Online Multilingual Dictionary using IndoWordNet
1
10
Automated analysis of Bangla poetry for classification and poet identification
21
11 11
12 59
13 4
14 22
15
An archaeological tour along the Ghaggar-Hakra River
5
16
Archaeology and history : essays in memory of Shri A. Ghosh
7
17 2
18 5
19 32
20 8

About Anupam Ghosh

Anupam Ghosh is a scholar working on Computer Vision and Pattern Recognition, Obstetrics and Gynecology and Media Technology, having authored 107 papers that have together received 972 indexed citations. Recurring topics across this work include Gene expression and cancer classification (25 papers), Bioinformatics and Genomic Networks (21 papers) and Machine Learning in Bioinformatics (17 papers). The work is most often cited by research in Obstetrics and Gynecology (135 citations), Genetics (175 citations) and Pediatrics, Perinatology and Child Health (269 citations). Anupam Ghosh has collaborated with scholars based in India, Hong Kong and China. Frequent co-authors include Swarup Kr Ghosh, Vivian Chan, J. S. K. Woo, Rajat K. De, Vivian Wong, S. J. Duthie, TK Chan, D. Todd, M. H. Y. Tang and Pak‐Cheong Ho. Their work appears in journals such as The Lancet, SHILAP Revista de lepidopterología and Blood.

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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