| Deep learning architecture based on segmented fundus image features for classification of diabetic retinopathy S Das, K Kharbanda, M Suchetha, R Raman, E Dhas Biomedical Signal Processing and Control 68, 102600, 2021 | 191 | 2021 |
| Real-time non-invasive detection and classification of diabetes using modified convolution neural network S Lekha, M Suchetha IEEE journal of biomedical and health informatics 22 (5), 1630-1636, 2017 | 109 | 2017 |
| Recent advancements and future prospects on e-nose sensors technology and machine learning approaches for non-invasive diabetes diagnosis: A review S Lekha, M Suchetha IEEE Reviews in Biomedical Engineering 14, 127-138, 2020 | 83 | 2020 |
| Empirical mode decomposition based filtering techniques for power line interference reduction in electrocardiogram using various adaptive structures and subtraction methods M Suchetha, N Kumaravel Biomedical Signal Processing and Control 8 (6), 575-585, 2013 | 82 | 2013 |
| PSO optimized 1-D CNN-SVM architecture for real-time detection and classification applications B Navaneeth, M Suchetha Computers in biology and medicine 108, 85-92, 2019 | 75 | 2019 |
| Real-time classification of healthy and apnea subjects using ECG signals with variational mode decomposition A Smruthy, M Suchetha IEEE sensors journal 17 (10), 3092-3099, 2017 | 59 | 2017 |
| A deep-learning-based system for automated sensing of chronic kidney disease N Bhaskar, S Manikandan IEEE Sensors Letters 3 (10), 1-4, 2019 | 55 | 2019 |
| Time series classification-based correlational neural network with bidirectional LSTM for automated detection of kidney disease N Bhaskar, M Suchetha, NY Philip IEEE Sensors Journal 21 (4), 4811-4818, 2020 | 45 | 2020 |
| A dynamic pooling based convolutional neural network approach to detect chronic kidney disease B Navaneeth, M Suchetha Biomedical Signal Processing and Control 62, 102068, 2020 | 40 | 2020 |
| A comparative analysis of EMD based filtering methods for 50 Hz noise cancellation in ECG signal M Suchetha, N Kumaravel, M Jagannath, SK Jaganathan Informatics in Medicine Unlocked 8, 54-59, 2017 | 40 | 2017 |
| A novel 1-D convolution neural network with SVM architecture for real-time detection applications S Lekha, M Suchetha IEEE sensors journal 18 (2), 724-731, 2017 | 37 | 2017 |
| A data analytics suite for exploratory predictive, and visual analysis of type 2 diabetes NY Philip, M Razaak, J Chang, M O’Kane, BK Pierscionek IEEE Access 10, 13460-13471, 2022 | 30 | 2022 |
| Vision Based Vehicle Detection: A Literature Review M Suchetha, JJ Antony International Journal of Applied Engineering Research 11 (5), 3128-3133, 2016 | 27* | 2016 |
| Sequential Convolutional Neural Networks for classification of cognitive tasks from EEG signals M Suchetha, R Madhumitha, R Sruthi Applied Soft Computing 111, 107664, 2021 | 25 | 2021 |
| A computationally efficient correlational neural network for automated prediction of chronic kidney disease N Bhaskar, M Suchetha IRBM 42 (4), 268-276, 2021 | 25 | 2021 |
| Non-invasive diabetes detection and classification using breath analysis Suchetha, Lekha ICCSP 1 (1), 0955-0958, 2015 | 22* | 2015 |
| An advanced gait monitoring system based on air pressure sensor embedded in a shoe B Abinaya, V Latha, M Suchetha Procedia engineering 38, 1634-1643, 2012 | 22 | 2012 |
| ECG arrhythmia detection and classification using relevance vector machine S Gayathri, M Suchetha, V Latha Procedia engineering 38, 1333-1339, 2012 | 21 | 2012 |
| A refined ResNet18 architecture with Swish activation function for Diabetic Retinopathy classification S Sunkari, A Sangam, M Suchetha, R Raman, R Rajalakshmi, ... Biomedical Signal Processing and Control 88, 105630, 2024 | 20 | 2024 |
| An approach for analysis and prediction of CKD using deep learning architecture N Bhaskar, M Suchetha 2019 International Conference on Communication and Electronics Systems …, 2019 | 19 | 2019 |
Lekha SrinivasanVIT UniversityVerified email at vit.ac.in