Anurag Jain

2.6k total citations · 1 hit paper
136 papers, 1.6k citations indexed

About

Anurag Jain is a scholar working on Artificial Intelligence, Information Systems and Surgery. According to data from OpenAlex, Anurag Jain has authored 136 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 26 papers in Information Systems and 22 papers in Surgery. Recurrent topics in Anurag Jain's work include Artificial Intelligence in Healthcare (16 papers), Cloud Computing and Resource Management (16 papers) and IoT and Edge/Fog Computing (13 papers). Anurag Jain is often cited by papers focused on Artificial Intelligence in Healthcare (16 papers), Cloud Computing and Resource Management (16 papers) and IoT and Edge/Fog Computing (13 papers). Anurag Jain collaborates with scholars based in India, United States and Saudi Arabia. Anurag Jain's co-authors include Rajneesh Kumar, Pooja Rani, Shamik Tiwari, Rohit Lamba, Nada Ahmed, Debipada Kabi, Tarun Gulati, Vivek Aggarwal, Harpal Randeva and Hisham Mehanna and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Anurag Jain

115 papers receiving 1.4k citations

Hit Papers

A decision support system for heart disease prediction ba... 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A decision support system for heart disease prediction based upon machine learning
    2021 199 citations Pooja Rani, Rajneesh Kumar et al. profile →

Peers

Anurag Jain
Kee Yuan Ngiam Singapore
Claire Cui United States
Thomas Neumuth Germany
Jinwook Choi South Korea
Thomas Ganslandt Germany
Matthieu Komorowski United Kingdom
Stavroula Mougiakakou Switzerland
İmran Kurt Türkiye
Santu Rana Australia
Sunil Gupta Australia
Kee Yuan Ngiam Singapore
Anurag Jain
Citations per year, relative to Anurag Jain Anurag Jain (= 1×) peers Kee Yuan Ngiam

Countries citing papers authored by Anurag Jain

Since Specialization
Citations

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

Fields of papers citing papers by Anurag Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anurag Jain

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

All Works

20 of 20 papers shown
1.
Tang, Zaiyong, et al.. (2024). A Comparative Study of Machine Learning Techniques for College Student Success Prediction. Journal of Higher Education Theory and Practice. 24(1). 3 indexed citations
2.
Tiwari, Shamik, et al.. (2024). HybridFusionNet: Deep Learning for Multi-Stage Diabetic Retinopathy Detection. SHILAP Revista de lepidopterología. 12(12). 256–256. 1 indexed citations
3.
4.
Kumar, Rajneesh, et al.. (2023). An adaptive framework for predicting breast cancer at an early stage. Measurement Sensors. 30. 100901–100901. 3 indexed citations
5.
Rani, Pooja, Rajneesh Kumar, Anurag Jain, et al.. (2023). PCA-DNN: A Novel Deep Neural Network Oriented System for Breast Cancer Classification. EAI Endorsed Transactions on Pervasive Health and Technology. 9. 6 indexed citations
6.
Rani, Pooja, Rajneesh Kumar, & Anurag Jain. (2022). A Hybrid Approach for Feature Selection Based on Correlation Feature Selection and Genetic Algorithm. International Journal of Software Innovation. 10(1). 1–17. 12 indexed citations
7.
Tiwari, Shamik & Anurag Jain. (2022). A lightweight capsule network architecture for detection of COVID‐19 from lung CT scans. International Journal of Imaging Systems and Technology. 32(2). 419–434. 19 indexed citations
8.
Lamba, Rohit, Tarun Gulati, & Anurag Jain. (2022). An Intelligent System for Parkinson's Diagnosis Using Hybrid Feature Selection Approach. International Journal of Software Innovation. 10(1). 1–13. 11 indexed citations
9.
Tiwari, Shamik, et al.. (2022). Diagnosing COVID-19 From Chest CT Scan Images Using Deep Learning Models. 11(2). 1–15. 2 indexed citations
10.
Rani, Pooja, Rajneesh Kumar, & Anurag Jain. (2022). A Hybrid System for Heart Disease Diagnosis Based on HPCBE Method. International Journal of Software Innovation. 10(1). 1–14. 5 indexed citations
11.
Kumar, Rajneesh, et al.. (2022). Breast cancer prediction based on neural networks and extra tree classifier using feature ensemble learning. Measurement Sensors. 24. 100560–100560. 33 indexed citations
12.
Kumar, Rajneesh, et al.. (2022). A QoS-Enabled Load Balancing Approach for Cloud Computing Environment Join Minimum Loaded Queue (JMLQ). International Journal of Grid and High Performance Computing. 14(1). 1–19. 1 indexed citations
13.
Rani, Pooja, et al.. (2021). A Hybrid Approach for Feature Selection Based on Genetic Algorithm and Recursive Feature Elimination. International Journal of Information System Modeling and Design. 12(2). 17–38. 25 indexed citations
14.
Rani, Pooja, Rajneesh Kumar, & Anurag Jain. (2021). HIOC: a hybrid imputation method to predict missing values in medical datasets. International Journal of Intelligent Computing and Cybernetics. 14(4). 598–616. 15 indexed citations
15.
Tiwari, Shamik, Anurag Jain, Akhilesh Sharma, & Khaled Mohamad Almustafa. (2021). Phonocardiogram Signal Based Multi-Class Cardiac Diagnostic Decision Support System. IEEE Access. 9. 110710–110722. 30 indexed citations
16.
Kumar, Rajneesh, et al.. (2020). A Proficient Approach for Load Balancing in Cloud Computing-Join Minimum Loaded Queue. International Journal of Information System Modeling and Design. 11(1). 12–36. 2 indexed citations
17.
Goswami, Puneet, et al.. (2019). A Comprehensive Review of Load Balancing Techniques in Cloud Computing and Their Simulation with CloudSim Plus. Recent Advances in Computer Science and Communications. 14(6). 1684–1694. 1 indexed citations
18.
Jain, Anurag, et al.. (2018). Hematoma in Urinary Bladder Masquerading as Neoplastic Mass. Indian Journal of Nuclear Medicine. 33(3). 253–254. 3 indexed citations
19.
Jain, Anurag, et al.. (2017). Role of 99m Tc MDP bone scan in delineation of ischaemic zone in cases of severe frostbite. Indian Journal of Nuclear Medicine. 32(3). 203–203. 1 indexed citations
20.
Jain, Anurag & Salvinder Singh. (2015). Effect of growth regulators and elicitors for the enhanced production of Solasodine in hairy root culture of Solanum melongena (L.). The Journal of Indian Botanical Society. 6 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.

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