Pranjul Yadav
About
In The Last Decade
Pranjul Yadav
19 papers receiving 386 citations
Peers
Comparison fields: 5 of 100
- Artificial Intelligence 172
- Epidemiology 151
- Health Information Management 71
- Surgery 47
- Molecular Biology 46
Countries citing papers authored by Pranjul Yadav
This map shows the geographic impact of Pranjul Yadav'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 Pranjul Yadav with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pranjul Yadav more than expected).
Fields of papers citing papers by Pranjul Yadav
This network shows the impact of papers produced by Pranjul Yadav. 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 Pranjul Yadav. The network helps show where Pranjul Yadav may publish in the future.
Co-authorship network of co-authors of Pranjul Yadav
This figure shows the co-authorship network connecting the top 25 collaborators of Pranjul Yadav. A scholar is included among the top collaborators of Pranjul Yadav based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pranjul Yadav. Pranjul Yadav is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | Conditional Generative Adversarial Networks for Regression | 6 |
| 5 | 5 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 175 | |
| 9 | 129 | |
| 10 | 1 | |
| 11 | 22 | |
| 12 | 3 | |
| 13 | A Data Mining Approach to Determine Sepsis Guideline Impact on Inpatient Mortality and Complications. | 8 |
| 14 | Predicting the Factors of Improvement of Health Status of Home Health Care Patients: A Holistic Data Mining Approach. | 1 |
| 15 | Clustering Health Data to Discover EBP Interventions for Sepsis Prevention and Treatment for Health Disparities. | 1 |
| 16 | 7 | |
| 17 | Data Mining Methodologies to Discover Best practices for Diabetic Patients with Health Disparities. | 1 |
| 18 | 14 | |
| 19 | 0 | |
| 20 | 3 |
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.