| Machine learning and deep learning approach for medical image analysis: diagnosis to detection M Rana, M Bhushan Multimedia Tools and Applications, 10.1007/s11042-022-14305-w, 2022 | 163 | 2022 |
| Latest tools for data mining and machine learning K Verma, S Bhardwaj, R Arya, UL Islam, M Bhushan, A Kumar, P Samant International Journal of Innovative Technology and Exploring Engineering 8 …, 2019 | 149 | 2019 |
| Intelligent Process Automation: The Future of Digital Transformation PS Kholiya, A Kapoor, M Rana, M Bhushan 2021 10th International Conference on System Modeling & Advancement in …, 2021 | 44 | 2021 |
| Real-Life Applications of the Internet of Things: Challenges, Applications, and Advances M Mangla, A Kumar, V Mehta, M Bhushan, SN Mohanty CRC Press, 2022 | 36 | 2022 |
| Prediction of Mortality from Heart Failure using Machine Learning MB Shyam Kedia 2022 2nd International Conference on Emerging Frontiers in Electrical and …, 2022 | 35 | 2022 |
| Intelligent Systems and Machine Learning for Industry: Advancements, Challenges, and Practices PR Anisha, CKK Reddy, NG Nguyen, M Bhushan, A Kumar, MM Hanafiah CRC Press, 2022 | 33 | 2022 |
| Smart Cities using Internet of Things: Recent Trends and Techniques AK Shagun Sharma, Mamta Nanda, Raghav Goel, Aashrey Jain, Megha Bhushan International Journal of Innovative Technology and Exploring Engineering 8 …, 2019 | 33* | 2019 |
| Classifying and resolving software product line redundancies using an ontological first-order logic rule based method M Bhushan, JÁG Duarte, P Samant, A Kumar, A Negi Expert Systems with Applications 168, 114167, 2021 | 30 | 2021 |
| Analyzing inconsistencies in software product lines using an ontological rule-based approach M Bhushan, S Goel, K Kaur Journal of Systems and Software 137, 605-617, 2018 | 30 | 2018 |
| Transformation from LEL to UML S Goel International Journal of Computer Applications 48 (12), 975-888, 2012 | 30* | 2012 |
| Deep Learning Techniques for Prediction and Diagnosis of Diabetes Mellitus MRAN S. Pal, N. Mishra, M. Bhushan, P. S. Kholiya 2022 International Mobile and Embedded Technology Conference (MECON), 588-593, 2022 | 29 | 2022 |
| Improving software product line using an ontological approach M Bhushan, S Goel Sādhanā 41 (12), 1381-1391, 2016 | 29 | 2016 |
| Advancements in Healthcare Services using Deep Learning Techniques M Rana, M Bhushan 2022 International Mobile and Embedded Technology Conference (MECON), 157-161, 2022 | 28 | 2022 |
| Improving quality of software product line by analysing inconsistencies in feature models using an ontological rule‐based approach M Bhushan, S Goel, A Kumar Expert Systems 35 (3), e12256, 2018 | 28 | 2018 |
| Prediction of students’ academic performance using Machine Learning Techniques U Verma, C Garg, M Bhushan, P Samant, AKA Negi 2022 International Mobile and Embedded Technology Conference (MECON), 151-156, 2022 | 27 | 2022 |
| A classification and systematic review of product line feature model defects M Bhushan, A Negi, P Samant, S Goel, A Kumar Software Quality Journal 28, 1507-1550, 2020 | 26 | 2020 |
| Managing software product line using an ontological rule-based framework M Bhushan, S Goel, A Kumar, A Negi 2017 International Conference on Infocom Technologies and Unmanned Systems …, 2017 | 26 | 2017 |
| Method to resolve software product line errors Megha, A Negi, K Kaur Information, Communication and Computing Technology: Second International …, 2017 | 26 | 2017 |
| Optimization of segment size assuring application perceived QoS in healthcare VJ Singh, M Bhushan, V Kumar, KL Bansal Proceedings of the world congress on engineering 1, 1-3, 2015 | 25 | 2015 |
| Deep Learning Techniques and Models for improving Machine Reading Comprehension System A Nalavade, A Bai, M Bhushan IJAST 29 (04), 9692-9710, 2020 | 24 | 2020 |