Saurabh Pal
- Health Information Management top 0.05%
- Artificial Intelligence in Healthcare 24
- Computer Science Applications top 0.5%
- Online Learning and Analytics 9
- Artificial Intelligence top 1%
- Imbalanced Data Classification Techniques 19
- AI in cancer detection 8
- Information Systems top 2%
- Data Mining Algorithms and Applications 10
- Spam and Phishing Detection 5
- Health Informatics top 10%
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- Advanced Fiber Optic Sensors 4
- Photonic and Optical Devices 4
Saurabh Pal
74 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Health Information Management 777
- Computer Science Applications 396
- Artificial Intelligence 1.0k
- Information Systems 423
- Health Informatics 20
Countries citing papers authored by Saurabh Pal
This map shows the geographic impact of Saurabh Pal'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 Saurabh Pal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saurabh Pal more than expected).
Fields of papers citing papers by Saurabh Pal
This network shows the impact of papers produced by Saurabh Pal. 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 Saurabh Pal. The network helps show where Saurabh Pal may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Saurabh Pal, 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 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 16 | |
| 4 | 2023 | 22 | |
| 5 | 2023 | 3 | |
| 6 | 2022 | 4 | |
| 7 | 2022 | 13 | |
| 8 | 2021 | 9 | |
| 9 | 2020 | 39 | |
| 10 | 2020 | 9 | |
| 11 | Chronic Kidney Disease: A Predictive Model Using Decision Tree | 2018 | 26 |
| 12 | 2018 | 16 | |
| 13 | A Novel Approach for Breast Cancer Detection Using Data Mining Techniques | 2017 | 103 |
| 14 | Performance Analysis of Data Mining Algorithms for Diagnosis and Prediction of Heart and Breast Cancer Disease | 2017 | 17 |
| 15 | Performance Analysis of Students Consuming Alcohol Using Data Mining Techniques | 2017 | 5 |
| 16 | Data Mining Approach to Detect Heart Diseases | 2014 | 81 |
| 17 | Data Mining Techniques: To Predict and Resolve Breast Cancer Survivability | 2014 | 113 |
| 18 | 2014 | 5 | |
| 19 | Early Prediction of Heart Diseases Using Data Mining Techniques | 2013 | 127 |
| 20 | The Modern Era: Online Pharmacy and Self Medication: Review | 2011 | 4 |
About Saurabh Pal
Saurabh Pal is a scholar working on Health Information Management, Computer Science Applications and Artificial Intelligence, having authored 78 papers that have together received 2.3k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (24 papers), Imbalanced Data Classification Techniques (19 papers), Data Mining Algorithms and Applications (10 papers), Online Learning and Analytics (9 papers), AI in cancer detection (8 papers), Spam and Phishing Detection (5 papers), Advanced Fiber Optic Sensors (4 papers) and Photonic and Optical Devices (4 papers). The work is most often cited by research in Health Information Management (777 citations), Computer Science Applications (396 citations) and Artificial Intelligence (1.0k citations). Saurabh Pal has collaborated with scholars based in India, United Kingdom and United States. Frequent co-authors include Vikas Chaurasia, Brijesh Kumar, B. B. Tiwari, Neha Singh, Tong Sun, K. T. V. Grattan, Scott A. Wade, Anil Kumar Soni, Kausar M. Ansari and A.T. Augousti. Their work appears in journals such as Life Sciences, Food Research International and Toxicology and Applied Pharmacology.
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.