Shubham Innani

33 total papers · 581 total citations
14 papers, 286 citations indexed

About

Shubham Innani is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Genetics. According to data from OpenAlex, Shubham Innani has authored 14 papers receiving a total of 286 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Artificial Intelligence and 3 papers in Genetics. Recurrent topics in Shubham Innani's work include Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (7 papers) and Glioma Diagnosis and Treatment (3 papers). Shubham Innani is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (7 papers) and Glioma Diagnosis and Treatment (3 papers). Shubham Innani collaborates with scholars based in United States and India. Shubham Innani's co-authors include Sanjay N. Talbar, Bhakti Baheti, Suhas Gajre, Spyridon Bakas, Ujjwal Baid, Sharath Chandra Guntuku, MacLean P. Nasrallah, William R. Bell and Mona Nasrallah and has published in prestigious journals such as Cancer Research, Scientific Reports and Pattern Recognition Letters.

In The Last Decade

Shubham Innani

12 papers receiving 273 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Shubham Innani 125 71 52 39 34 14 286
Kun Huang 107 0.9× 70 1.0× 66 1.3× 20 0.5× 17 0.5× 23 309
Yurong Guo 103 0.8× 100 1.4× 36 0.7× 7 0.2× 27 0.8× 18 285
Boxiong Yang 135 1.1× 51 0.7× 18 0.3× 41 1.1× 32 0.9× 19 305
Yanhong Luo 128 1.0× 101 1.4× 86 1.7× 8 0.2× 54 1.6× 7 318
Dongju Liu 84 0.7× 34 0.5× 21 0.4× 12 0.3× 29 0.9× 17 288
A.G. Shanbhag 76 0.6× 114 1.6× 21 0.4× 12 0.3× 28 0.8× 14 311
Jia Xue 220 1.8× 56 0.8× 20 0.4× 29 0.7× 31 0.9× 12 326
Philomina Simon 136 1.1× 71 1.0× 31 0.6× 19 0.5× 52 1.5× 30 280
Chen Shen 72 0.6× 35 0.5× 19 0.4× 17 0.4× 30 0.9× 19 212
C H Chen 173 1.4× 74 1.0× 22 0.4× 18 0.5× 48 1.4× 6 330

Countries citing papers authored by Shubham Innani

Since Specialization
Citations

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

Fields of papers citing papers by Shubham Innani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shubham Innani

This figure shows the co-authorship network connecting the top 25 collaborators of Shubham Innani. A scholar is included among the top collaborators of Shubham Innani 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 Shubham Innani. Shubham Innani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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