| Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review B Jena, S Saxena, GK Nayak, L Saba, N Sharma, JS Suri Computers in Biology and Medicine 137, 104803, 2021 | 121 | 2021 |
| An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review S Das, GK Nayak, L Saba, M Kalra, JS Suri, S Saxena Computers in biology and medicine 143, 105273, 2022 | 84 | 2022 |
| Role of artificial intelligence in radiogenomics for cancers in the era of precision medicine S Saxena, B Jena, N Gupta, S Das, D Sarmah, P Bhattacharya, T Nath, ... Cancers 14 (12), 2860, 2022 | 62 | 2022 |
| Review of brain tumor segmentation and classification N Kumari, S Saxena 2018 International conference on current trends towards converging …, 2018 | 57 | 2018 |
| Image processing tasks using parallel computing in multi core architecture and its applications in medical imaging S Saxena, N Sharma, S Sharma International Journal of Advanced Research in Computer and Communication …, 2013 | 57 | 2013 |
| Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review JS Suri, M Bhagawati, S Paul, A Protogeron, PP Sfikakis, GD Kitas, ... Computers in biology and medicine 142, 105204, 2022 | 47 | 2022 |
| An empirical study of different machine learning techniques for brain tumor classification and subsequent segmentation using hybrid texture feature B Jena, GK Nayak, S Saxena Machine Vision and Applications 33 (1), 6, 2022 | 47 | 2022 |
| Bias Investigation in Artificial Intelligence Systems for Early Detection of Parkinson’s Disease: A Narrative Review S Paul, M Maindarkar, S Saxena, L Saba, M Turk, M Kalra, P R. Krishnan, ... Diagnostics 12 (166), 1-25, 2022 | 45 | 2022 |
| Research Article Parallel Image Processing Techniques, Benefits and Limitations S Saxena, S Sharma, N Sharma Research Journal of Applied Sciences, Engineering and Technology 12 (2), 223-238, 2016 | 45 | 2016 |
| Applications of radiomics and radiogenomics in high-grade gliomas in the era of precision medicine A Fathi Kazerooni, SJ Bagley, H Akbari, S Saxena, S Bagheri, J Guo, ... Cancers 13 (23), 5921, 2021 | 41 | 2021 |
| Brain tumor characterization using radiogenomics in artificial intelligence framework B Jena, S Saxena, GK Nayak, A Balestrieri, N Gupta, NN Khanna, ... Cancers 14 (16), 4052, 2022 | 38 | 2022 |
| A powerful paradigm for cardiovascular risk stratification using multiclass, multi-label, and ensemble-based machine learning paradigms: A narrative review JS Suri, M Bhagawati, S Paul, AD Protogerou, PP Sfikakis, GD Kitas, ... Diagnostics 12 (3), 722, 2022 | 37 | 2022 |
| Five Strategies for Bias Estimation in Artificial Intelligence-based Hybrid Deep Learning for Acute Respiratory Distress Syndrome COVID-19 Lung Infected Patients using AP(ai … J S. Suri, S Agarwal, B Jena, S Saxena, A El-Baz, V Agarwal, M K. Kalra, ... IEEE Transactions on Instrumentation and Measurement, 1-11, 2022 | 34 | 2022 |
| Brain tumor segmentation and overall survival period prediction in glioblastoma multiforme using radiomic features S Das, S Bose, GK Nayak, SC Satapathy, S Saxena Concurrency and Computation: Practice and Experience 34 (20), e6501, 2022 | 32 | 2022 |
| Cardiovascular/stroke risk stratification in Parkinson’s disease patients using atherosclerosis pathway and artificial intelligence paradigm: A systematic review JS Suri, S Paul, MA Maindarkar, A Puvvula, S Saxena, L Saba, M Turk, ... Metabolites 12 (4), 312, 2022 | 31 | 2022 |
| Convolutional neural network and its pretrained models for image classification and object detection: A survey B Jena, GK Nayak, S Saxena Concurrency and Computation: Practice and Experience, e6767, 2021 | 31 | 2021 |
| Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastoma A Fathi Kazerooni, S Saxena, E Toorens, D Tu, V Bashyam, H Akbari, ... Scientific Reports 12 (1), 8784, 2022 | 29 | 2022 |
| Validation of random dataset using an efficient CNN model trained on MNIST handwritten dataset A Garg, D Gupta, S Saxena, PP Sahadev 2019 6th international conference on signal processing and integrated …, 2019 | 26 | 2019 |
| Brain tumour segmentation in FLAIR MRI using sliding window texture feature extraction followed by fuzzy C-means clustering S Saxena, N Kumari, S Pattnaik International Journal of Healthcare Information Systems and Informatics …, 2021 | 24 | 2021 |
| Medical image segmentation: hard and soft computing approaches P Sinha, M Tuteja, S Saxena SN Applied Sciences 2, 1-8, 2020 | 21 | 2020 |
Jasjit Suri PhD MBA, FIEEE, FAIMBE,...Global Biomedical Technologies, Inc., CA, USA; Computer Engineering Dept., Idaho State University在 AtheroPoint.com 的电子邮件经过验证
