Abrar Gani

3 papers and 40 indexed citations i.

About

Abrar Gani is a scholar working on Surgery, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Abrar Gani has authored 3 papers receiving a total of 40 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Surgery, 1 paper in Biomedical Engineering and 1 paper in Artificial Intelligence. Recurrent topics in Abrar Gani’s work include COVID-19 diagnosis using AI (1 paper), Anatomy and Medical Technology (1 paper) and Machine Learning in Healthcare (1 paper). Abrar Gani is often cited by papers focused on COVID-19 diagnosis using AI (1 paper), Anatomy and Medical Technology (1 paper) and Machine Learning in Healthcare (1 paper). Abrar Gani collaborates with scholars based in United Kingdom and India. Abrar Gani's co-authors include Philip H. Pucher, Andrea Annoni, Sukhpal Singh Gill, Steve Uhlig, Rajesh Arya, Deepraj Chowdhury, Georgia Lucas and Marie J. Parsons and has published in prestigious journals such as Annals of Medicine and Surgery, PubMed and Internet Technology Letters.

In The Last Decade

Co-authorship network of co-authors of Abrar Gani i

Fields of papers citing papers by Abrar Gani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Abrar Gani

Since Specialization
Citations

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

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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2025