Madhvan Bajaj

576 total citations
19 papers, 186 citations indexed

About

Madhvan Bajaj is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Health Information Management. According to data from OpenAlex, Madhvan Bajaj has authored 19 papers receiving a total of 186 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Health Information Management. Recurrent topics in Madhvan Bajaj's work include Artificial Intelligence in Healthcare (5 papers), AI in cancer detection (5 papers) and COVID-19 diagnosis using AI (4 papers). Madhvan Bajaj is often cited by papers focused on Artificial Intelligence in Healthcare (5 papers), AI in cancer detection (5 papers) and COVID-19 diagnosis using AI (4 papers). Madhvan Bajaj collaborates with scholars based in India, United Kingdom and United States. Madhvan Bajaj's co-authors include Priyanshu Rawat, Vikrant Sharma, Satvik Vats, Rahul Chauhan, Teekam Singh, Bharat Bhushan Sagar, Chandradeep Bhatt, Prerna Prerna, Rakesh Kumar and Saket Srivastava and has published in prestigious journals such as Journal of Information and Optimization Sciences.

In The Last Decade

Madhvan Bajaj

18 papers receiving 177 citations

Peers

Madhvan Bajaj

AI

CNC

HIM

RNMI

IS

Priyanshu Rawat India

S. M. Nuruzzaman Nobel Bangladesh

Martina Iammarino Italy

S M Masfequier Rahman Swapno Bangladesh

Satyajit Mahapatra India

Dhananjay Bisen India

K Ananthajothi India

Mani Abedini Australia

Manoranjan Parhi India

Nitesh Pradhan India

Priyanshu Rawat India

Madhvan Bajaj

76 ×1.2

AI

43 ×1.1

CNC

32 ×1.1

HIM

35 ×1.3

RNMI

27 ×1.1

IS

Citations per year, relative to Madhvan Bajaj Madhvan Bajaj (= 1×) peers Priyanshu Rawat

Countries citing papers authored by Madhvan Bajaj

Since Specialization

Citations

This map shows the geographic impact of Madhvan Bajaj'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 Madhvan Bajaj with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Madhvan Bajaj more than expected).

Fields of papers citing papers by Madhvan Bajaj

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Madhvan Bajaj. 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 Madhvan Bajaj. The network helps show where Madhvan Bajaj may publish in the future.

Co-authorship network of co-authors of Madhvan Bajaj

This figure shows the co-authorship network connecting the top 25 collaborators of Madhvan Bajaj. A scholar is included among the top collaborators of Madhvan Bajaj 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 Madhvan Bajaj. Madhvan Bajaj is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

1.

Rawat, Priyanshu, et al.. (2023). A Study on Cervical Cancer Prediction using Various Machine Learning Approaches. 1101–1107. 18 indexed citations

2.

Sharma, Vikrant, Satvik Vats, Priyanshu Rawat, & Madhvan Bajaj. (2023). Crop recommendation system: A review. 384–396. 5 indexed citations

3.

Rawat, Priyanshu, et al.. (2023). A Study on Liver Disease Using Different Machine Learning Algorithms. 22. 721–727. 7 indexed citations

4.

Vats, Satvik, et al.. (2023). Intelligent System for Identification and Classification of Pneumonia using Machine Learning. 1–6. 1 indexed citations

5.

Bajaj, Madhvan, et al.. (2023). Prediction of Mental Health Treatment Adherence using Machine Learning Algorithms. 716–720. 11 indexed citations

6.

Bajaj, Madhvan, et al.. (2023). Classification And Prediction of Brain Tumors and its Types using Deep Learning. 705–710. 13 indexed citations

7.

Rawat, Priyanshu, et al.. (2023). An Analysis of Crop Recommendation Systems Employing Diverse Machine Learning Methodologies. 619–624. 21 indexed citations

8.

Rawat, Priyanshu, Madhvan Bajaj, Vikrant Sharma, & Satvik Vats. (2023). A Comprehensive Analysis of the Effectiveness of Machine Learning Algorithms for Predicting Water Quality. 1108–1114. 21 indexed citations

9.

Rawat, Priyanshu, Madhvan Bajaj, Satvik Vats, & Vikrant Sharma. (2023). ASD Diagnosis in Children, Adults, and Adolescents using Various Machine Learning Techniques. 625–630. 17 indexed citations

10.

Bajaj, Madhvan, Priyanshu Rawat, Vikrant Sharma, et al.. (2023). Study on Degenerative Parkinson's Disease Using Various Machine Learning Algorithms. 1–6.

11.

Bajaj, Madhvan, et al.. (2023). Enhancing patient outcomes through machine learning: A study of lung cancer prediction. Journal of Information and Optimization Sciences. 44(6). 1075–1086. 15 indexed citations

12.

Bajaj, Madhvan, et al.. (2023). A Study on Tuberculosis With Deep Learning and Machine Learning Approaches. 1–6. 1 indexed citations

13.

Bajaj, Madhvan, et al.. (2023). Comparative Analytic Study of Machine Learning Algorithms for PCOS Diagnosis and Outcome Prediction: An Empirical Analysis. 391–397. 3 indexed citations

14.

Rawat, Priyanshu, et al.. (2023). Optimizing Hypothyroid Diagnosis with Physician-Supervised Feature Reduction using Machine Learning Techniques. 711–715. 8 indexed citations

15.

Vats, Satvik, et al.. (2023). Crop Prediction Using Ensemble Learning. 90–95. 4 indexed citations

16.

Rawat, Priyanshu, Madhvan Bajaj, Satvik Vats, & Vikrant Sharma. (2023). A comprehensive study based on MFCC and spectrogram for audio classification. Journal of Information and Optimization Sciences. 44(6). 1057–1074. 19 indexed citations

17.

Rawat, Priyanshu, et al.. (2023). Predicting Breast Cancer An Evaluation of Machine Learning Approaches. 1–8. 1 indexed citations

18.

Bajaj, Madhvan, Priyanshu Rawat, Chandradeep Bhatt, Rahul Chauhan, & Teekam Singh. (2023). Heart Disease Prediction using Ensemble ML. 680–685. 14 indexed citations

19.

Rawat, Priyanshu, et al.. (2023). Cancer Malignancy Prediction Using Machine Learning: A Cross-Dataset Comparative Study. 699–704. 7 indexed citations

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.

Explore authors with similar magnitude of impact