Vaishnavi Singh

1.2k citations
6 papers · 823 indexed · 2 hit papers · h-index 3
Topics
COVID-19 and healthcare impacts (2 papers)COVID-19 diagnosis using AI (2 papers)AI in cancer detection (2 papers)
Partner nations
IndiaMexico

In The Last Decade

Vaishnavi Singh

3 papers receiving 794 citations

Hit Papers

Application of deep learning for fast detection of COVID-...202020262022202420202020100200300400

Peers

Vaishnavi Singh
Comparison fields: 5 of 97
  • Radiology, Nuclear Medicine and Imaging 681
  • Artificial Intelligence 471
  • Health Informatics 146
  • Computer Vision and Pattern Recognition 119
  • Pulmonary and Respiratory Medicine 90
Replace Jinlu Ma with:
Jinlu Ma China
Huan Yuan China
Muskan Goyal India
Amanullah Asraf Bangladesh
Md. Zabirul Islam Bangladesh
Abolfazl Zargari Khuzani United States
Ziwang Huang China
Neha Gianchandani Canada
Soham Taneja India
Xiaoming Qiu China
Vaishnavi Singh relative to Jinlu Ma China Jinlu Ma's profile →
Citations per field
00.5×1.5×2.3×
Jinlu Ma · 1×
Citations per year

Countries citing papers authored by Vaishnavi Singh

Since Specialization
Citations

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

Fields of papers citing papers by Vaishnavi Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vaishnavi Singh

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

All Works

6 of 6 papers shown
#WorkIndexed citations
1 0
2 1
3 0
4 6
5
A deep learning and grad-CAM based color visualization approach for fast detection of COVID-19 cases using chest X-ray and CT-Scan imagesbreakdown →
356
6
Application of deep learning for fast detection of COVID-19 in X-Rays using nCOVnetbreakdown →
460

About Vaishnavi Singh

Vaishnavi Singh is a scholar working on Management Information Systems, Computer Vision and Pattern Recognition and Information Systems, having authored 6 papers that have together received 823 indexed citations. Recurring topics across this work include COVID-19 and healthcare impacts (2 papers), COVID-19 diagnosis using AI (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (146 citations), Radiology, Nuclear Medicine and Imaging (681 citations) and Artificial Intelligence (471 citations). Vaishnavi Singh has collaborated with scholars based in India and Mexico. Frequent co-authors include Rubén Morales-Menéndez, P. K. Gupta, Mohammad Khubeb Siddiqui, Prakhar Bhardwaj, Deepak Gupta and Nitin Joseph. Their work appears in journals such as Chaos Solitons & Fractals, International Journal of Interactive Multimedia and Artificial Intelligence and International Journal of Academic Medicine.

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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