Ujjwal Baid
Impact in
- Neurology top 5%
- Brain Tumor Detection and Classification
- Health Informatics top 10%
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 9
- COVID-19 diagnosis using AI 3
-
- Medical Image Segmentation Techniques 4
- Advanced Neural Network Applications 4
- Co-authors
- Sanjay N. Talbar (14 shared papers)Sudeep Gupta (2 shared papers)Meenakshi Thakur (2 shared papers)Swapnil Rane (2 shared papers)Aliasgar Moiyadi (2 shared papers)Abhishek Mahajan (3 shared papers)Spyridon Bakas (8 shared papers)Bhakti Baheti (7 shared papers)
- Journals
- Scientific Reports (1 paper)Neuro-Oncology (1 paper)Biomedical Signal Processing and Control (1 paper)Radiology Artificial Intelligence (1 paper)Physics in Medicine and Biology (1 paper)
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Ujjwal Baid
23 papers receiving 495 citations
Peers
Comparison fields: 5 of 65
- Neurology 123
- Health Informatics 15
- Radiology, Nuclear Medicine and Imaging 234
- Genetics 83
- Computer Vision and Pattern Recognition 141
Countries citing papers authored by Ujjwal Baid
This map shows the geographic impact of Ujjwal Baid'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 Ujjwal Baid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ujjwal Baid more than expected).
Fields of papers citing papers by Ujjwal Baid
This network shows the impact of papers produced by Ujjwal Baid. 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 Ujjwal Baid. The network helps show where Ujjwal Baid may publish in the future.
Co-authors
The 25 scholars most cited alongside Ujjwal Baid, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 93 | |
| 2 | 2020 | 83 | |
| 3 | 2022 | 81 | |
| 4 | 2021 | 65 | |
| 5 | 2021 | 35 | |
| 6 | 2021 | 22 | |
| 7 | 2022 | 19 | |
| 8 | 2023 | 18 | |
| 9 | 2019 | 16 | |
| 10 | 2017 | 16 | |
| 11 | 2016 | 11 | |
| 12 | 2020 | 9 | |
| 13 | 2023 | 8 | |
| 14 | 2023 | 7 | |
| 15 | 2017 | 7 | |
| 16 | 2021 | 6 | |
| 17 | 2021 | 4 | |
| 18 | 2015 | 4 | |
| 19 | 2017 | 3 | |
| 20 | 2022 | 3 |
About Ujjwal Baid
Ujjwal Baid is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Neurology, Artificial Intelligence and Pulmonary and Respiratory Medicine, having authored 24 papers that have together received 513 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), Brain Tumor Detection and Classification (7 papers), Medical Image Segmentation Techniques (4 papers), Advanced Neural Network Applications (4 papers), Lung Cancer Diagnosis and Treatment (4 papers), COVID-19 diagnosis using AI (3 papers), Glioma Diagnosis and Treatment (3 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Neurology (123 citations), Health Informatics (15 citations), Radiology, Nuclear Medicine and Imaging (234 citations), Genetics (83 citations) and Computer Vision and Pattern Recognition (141 citations). Ujjwal Baid has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Sanjay N. Talbar, Sudeep Gupta, Meenakshi Thakur, Swapnil Rane, Aliasgar Moiyadi, Abhishek Mahajan, Spyridon Bakas, Bhakti Baheti, Soonmee Cha and Javier Villanueva-Meyer. Their work appears in journals such as Scientific Reports, Neuro-Oncology, Biomedical Signal Processing and Control, Radiology Artificial Intelligence and Physics in Medicine and Biology.
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.