Pallavi Goel
Impact in
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- Artificial Intelligence in Healthcare
Papers in
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- AI in cancer detection 3
- Co-authors
- Devvret Verma (1 shared paper)Ramgopal Kashyap (1 shared paper)Syam Machinathu Parambil Gangadharan (1 shared paper)Sameer Alshehri (1 shared paper)Majed A. Algarni (1 shared paper)Awal Halifa (1 shared paper)Amena Mahmoud (1 shared paper)Surjeet Dalal (1 shared paper)
- Journals
- Computational Intelligence and Neuroscience (2 papers)Measurement and Control (1 paper)BMJ Case Reports (1 paper)SSRN Electronic Journal (5 papers)E3S Web of Conferences (1 paper)
- Partner nations
- IndiaSaudi ArabiaIraq
In The Last Decade
Pallavi Goel
15 papers receiving 177 citations
Peers
Comparison fields: 5 of 69
- Health Information Management 36
- Medical Laboratory Technology 5
- Artificial Intelligence 51
- Computer Networks and Communications 27
- Information Systems 24
Countries citing papers authored by Pallavi Goel
This map shows the geographic impact of Pallavi Goel'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 Pallavi Goel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pallavi Goel more than expected).
Fields of papers citing papers by Pallavi Goel
This network shows the impact of papers produced by Pallavi Goel. 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 Pallavi Goel. The network helps show where Pallavi Goel may publish in the future.
Co-authors
The 24 scholars most cited alongside Pallavi Goel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 108 | |
| 2 | 2023 | 39 | |
| 3 | 2020 | 8 | |
| 4 | Comparison of Classification Techniques on Data Mining | 2019 | 6 |
| 5 | 2020 | 5 | |
| 6 | 2021 | 4 | |
| 7 | Comparative Analysis of Heart Disease Prediction | 2019 | 3 |
| 8 | 2023 | 3 | |
| 9 | 2020 | 3 | |
| 10 | 2020 | 2 | |
| 11 | 2023 | 2 | |
| 12 | 2016 | 2 | |
| 13 | Crack Detection and Diagnosis for Wind Turbines Using Naive | 2019 | 1 |
| 14 | 2023 | 1 | |
| 15 | 2020 | 1 | |
| 16 | 2024 | 0 |
About Pallavi Goel
Pallavi Goel is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Health Information Management and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 188 indexed citations. Recurring topics across this work include AI in cancer detection (3 papers), Medical Image Segmentation Techniques (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Artificial Intelligence in Healthcare (2 papers), Recycling and Waste Management Techniques (1 paper), Risk and Safety Analysis (1 paper), Engineering Diagnostics and Reliability (1 paper) and COVID-19 epidemiological studies (1 paper). The work is most often cited by research in Health Information Management (36 citations), Medical Laboratory Technology (5 citations), Artificial Intelligence (51 citations), Computer Networks and Communications (27 citations) and Information Systems (24 citations). Pallavi Goel has collaborated with scholars based in India, Saudi Arabia and Iraq. Frequent co-authors include Devvret Verma, Ramgopal Kashyap, Syam Machinathu Parambil Gangadharan, Sameer Alshehri, Majed A. Algarni, Awal Halifa, Amena Mahmoud, Surjeet Dalal, Edeh Michael Onyema and Prashant Johri. Their work appears in journals such as Computational Intelligence and Neuroscience, Measurement and Control, BMJ Case Reports, SSRN Electronic Journal and E3S Web of Conferences.
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.