Gopichandh Danala
- Health Informatics top 2%
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- Radiomics and Machine Learning in Medical Imaging 17
- Artificial Intelligence top 5%
- AI in cancer detection 16
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- Intracranial Aneurysms: Treatment and Complications 3
- Traumatic Brain Injury and Neurovascular Disturbances 3
- Health Information Management top 10%
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- Digital Radiography and Breast Imaging 4
- Gastric Cancer Management and Outcomes 3
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- Gene expression and cancer classification 3
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- Stroke Rehabilitation and Recovery 2
- Co-authors
- Bin ZhengMorteza HeidariSeyedehnafiseh MirniaharikandeheiYuchen QiuAbolfazl Zargari KhuzaniHong LiuS. LakshmivarahanTeresa Wu
- Journals
- SHILAP Revista de lepidopterología (1 paper)Scientific Reports (1 paper)IEEE Transactions on Biomedical Engineering (1 paper)
- Partner nations
- United StatesIran
In The Last Decade
Gopichandh Danala
35 papers receiving 638 citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Health Informatics 53
- Radiology, Nuclear Medicine and Imaging 447
- Artificial Intelligence 342
- Neurology 50
- Health Information Management 21
Countries citing papers authored by Gopichandh Danala
This map shows the geographic impact of Gopichandh Danala'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 Gopichandh Danala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gopichandh Danala more than expected).
Fields of papers citing papers by Gopichandh Danala
This network shows the impact of papers produced by Gopichandh Danala. 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 Gopichandh Danala. The network helps show where Gopichandh Danala may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gopichandh Danala, 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 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 1 | |
| 5 | 2022 | 22 | |
| 6 | 2022 | 4 | |
| 7 | 2022 | 11 | |
| 8 | 2022 | 4 | |
| 9 | 2021 | 37 | |
| 10 | 2021 | 19 | |
| 11 | 2021 | 1 | |
| 12 | 2021 | 3 | |
| 13 | Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithmsbreakdown → | 2020 | 290 |
| 14 | 2019 | 11 | |
| 15 | 2019 | 25 | |
| 16 | 2019 | 5 | |
| 17 | 2019 | 13 | |
| 18 | 2018 | 58 | |
| 19 | 2017 | 36 | |
| 20 | 2017 | 62 |
About Gopichandh Danala
Gopichandh Danala is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Artificial Intelligence, having authored 35 papers that have together received 654 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (17 papers), AI in cancer detection (16 papers), Digital Radiography and Breast Imaging (4 papers), Intracranial Aneurysms: Treatment and Complications (3 papers), Traumatic Brain Injury and Neurovascular Disturbances (3 papers), Gastric Cancer Management and Outcomes (3 papers), Gene expression and cancer classification (3 papers) and Stroke Rehabilitation and Recovery (2 papers). The work is most often cited by research in Health Informatics (53 citations), Radiology, Nuclear Medicine and Imaging (447 citations) and Artificial Intelligence (342 citations). Gopichandh Danala has collaborated with scholars based in United States and Iran. Frequent co-authors include Bin Zheng, Morteza Heidari, Seyedehnafiseh Mirniaharikandehei, Yuchen Qiu, Abolfazl Zargari Khuzani, Hong Liu, S. Lakshmivarahan, Teresa Wu, Bhavika Patel and Alan B. Hollingsworth. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Biomedical Engineering.
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.