Bi-objective approach for computer-aided diagnosis of schizophrenia patients using fMRI data I Chatterjee, M Agarwal, B Rana, N Lakhyani, N Kumar Multimedia Tools and Applications 77, 26991-27015, 2018 | 40 | 2018 |
Cov-elm classifier: an extreme learning machine based identification of covid-19 using chest x-ray images S Rajpal, M Agarwal, A Rajpal, N Lakhyani, A Saggar, N Kumar Intelligent Decision Technologies 16 (1), 193-203, 2022 | 38 | 2022 |
Identification of brain regions associated with working memory deficit in schizophrenia I Chatterjee, V Kumar, S Sharma, D Dhingra, B Rana, M Agarwal, ... F1000Research 8, 2019 | 34 | 2019 |
Parallel multi-objective multi-robot coalition formation M Agarwal, N Agrawal, S Sharma, L Vig, N Kumar Expert Systems with Applications 42 (21), 7797-7811, 2015 | 32 | 2015 |
Non-additive multi-objective robot coalition formation M Agarwal, N Kumar, L Vig Expert Systems with Applications 41 (8), 3736-3747, 2014 | 29 | 2014 |
Identification of changes in grey matter volume using an evolutionary approach: an MRI study of schizophrenia I Chatterjee, V Kumar, B Rana, M Agarwal, N Kumar Multimedia Systems 26 (4), 383-396, 2020 | 23 | 2020 |
Impact of ageing on the brain regions of the schizophrenia patients: an fMRI study using evolutionary approach I Chatterjee, V Kumar, B Rana, M Agarwal, N Kumar Multimedia Tools and Applications 79, 24757-24779, 2020 | 21 | 2020 |
An explainable AI-driven biomarker discovery framework for Non-Small Cell Lung Cancer classification K Dwivedi, A Rajpal, S Rajpal, M Agarwal, V Kumar, N Kumar Computers in Biology and Medicine 153, 106544, 2023 | 16 | 2023 |
Triphasic deepbrca-a deep learning-based framework for identification of biomarkers for breast cancer stratification S Rajpal, M Agarwal, V Kumar, A Gupta, N Kumar IEEE Access 9, 103347-103364, 2021 | 12 | 2021 |
MOEA for discovering Pareto-optimal process models: an experimental comparison S Deshmukh, M Agarwal, S Gupta, N Kumar International Journal of Computational Science and Engineering 21 (3), 446-456, 2020 | 9 | 2020 |
XAI-MethylMarker: Explainable AI approach for biomarker discovery for breast cancer subtype classification using methylation data S Rajpal, A Rajpal, A Saggar, AK Vaid, V Kumar, M Agarwal, N Kumar Expert Systems with Applications 225, 120130, 2023 | 5 | 2023 |
Synthesis, structure and physico-chemical studies of Mn (II) complexes of salicylaldehyde derived semicarbazone and thiosemicarbazone NK Sharma, AM Sapna, M Agarwal, S Kohli, B Tiwari, JN Gurtu, ... Oriental Journal of Chemistry 26 (1), 103-108, 2010 | 5 | 2010 |
XAI-CNVMarker: Explainable AI-based copy number variant biomarker discovery for breast cancer subtypes S Rajpal, A Rajpal, M Agarwal, V Kumar, A Abraham, D Khanna, N Kumar Biomedical Signal Processing and Control 84, 104979, 2023 | 4 | 2023 |
Deep learning based model for breast cancer subtype classification S Rajpal, V Kumar, M Agarwal, N Kumar arXiv preprint arXiv:2111.03923, 2021 | 4 | 2021 |
Multi-objective robot coalition formation for non-additive environments M Agarwal, L Vig, N Kumar International Conference on Intelligent Robotics and Applications, 346-355, 2011 | 4 | 2011 |
Enlightening the path to NSCLC biomarkers: Utilizing the power of XAI-guided deep learning K Dwivedi, A Rajpal, S Rajpal, V Kumar, M Agarwal, N Kumar Computer Methods and Programs in Biomedicine 243, 107864, 2024 | 3 | 2024 |
Study of working memory impairment in schizophrenia patients I Chatterjee, B Rana, M Agarwal, N Kumar F1000Research 9 (787), 2020 | 2 | 2020 |
Multiple objective robot coalition formation M Agarwal, L Vig, N Kumar Walter de Gruyter GmbH & Co. KG 20 (4), 395-413, 2011 | 2 | 2011 |
I-LDD: an interpretable leaf disease detector R Mishra, Kavita, A Rajpal, V Bhatia, S Rajpal, M Agarwal, N Kumar Soft Computing 28 (3), 2517-2533, 2024 | 1 | 2024 |
I-flash: Interpretable fake news detector using lime and shap V Dua, A Rajpal, S Rajpal, M Agarwal, N Kumar Wireless Personal Communications 131 (4), 2841-2874, 2023 | 1 | 2023 |