| A deep learning approach for real-time detection of atrial fibrillation RS Andersen, A Peimankar, S Puthusserypady Expert Systems with Applications 115, 465-473, 2019 | 362 | 2019 |
| DENS-ECG: A deep learning approach for ECG signal delineation A Peimankar, S Puthusserypady Expert systems with applications 165, 113911, 2021 | 125 | 2021 |
| Evolutionary multi-objective fault diagnosis of power transformers A Peimankar, SJ Weddell, T Jalal, AC Lapthorn Swarm and Evolutionary Computation 36, 62-75, 2017 | 91 | 2017 |
| Multi-objective ensemble forecasting with an application to power transformers A Peimankar, SJ Weddell, T Jalal, AC Lapthorn Applied Soft Computing 68, 233-248, 2018 | 44 | 2018 |
| An ensemble of deep recurrent neural networks for p-wave detection in electrocardiogram A Peimankar, S Puthusserypady ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 23 | 2019 |
| Ensemble classifier selection using multi-objective PSO for fault diagnosis of power transformers A Peimankar, SJ Weddell, T Jalal, AC Lapthorn 2016 IEEE congress on evolutionary computation (CEC), 3622-3629, 2016 | 22 | 2016 |
| Short-term atrial fibrillation detection using electrocardiograms: A comparison of machine learning approaches MS Jahan, M Mansourvar, S Puthusserypady, UK Wiil, A Peimankar International Journal of Medical Informatics 163, 104790, 2022 | 18 | 2022 |
| Deepaware: A hybrid deep learning and context-aware heuristics-based model for atrial fibrillation detection D Kumar, A Peimankar, K Sharma, H Domínguez, S Puthusserypady, ... Computer Methods and Programs in Biomedicine 221, 106899, 2022 | 18 | 2022 |
| Ensemble learning for detection of short episodes of atrial fibrillation A Peimankar, S Puthusserypady 2018 26th European Signal Processing Conference (EUSIPCO), 66-70, 2018 | 16 | 2018 |
| Automatic detection of cardiac arrhythmias using ensemble learning A Peimankar, MJ Jajroodi, S Puthusserypady TENCON 2019-2019 IEEE Region 10 Conference (TENCON), 383-388, 2019 | 12 | 2019 |
| The influence of corona near to the bushing of a transformer on partial discharge measurement with an acoustic emission sensor SAM Najafi, A Peimankar, H Saadati, E Gockenbach, H Borsi 2013 IEEE Electrical Insulation Conference (EIC), 295-298, 2013 | 11 | 2013 |
| Condition Assessment of Transformers Load Tap Changers Using Support Vector Machine A Peimankar, A Lapthorn The 19th International Symposium on High Voltage Engineering (ISH 2015), 2015 | 8 | 2015 |
| An isolated hybrid renewable energy system: Ha'apai island group in the Kingdom of Tonga X Cao, A Lapthorn, A Peimankar The 2nd IEEE Conference on Power Engineering and Renewable Energy (ICPERE …, 2014 | 7 | 2014 |
| A machine learning approach for walking classification in elderly people with gait disorders A Peimankar, TS Winther, A Ebrahimi, UK Wiil Sensors 23 (2), 679, 2023 | 6 | 2023 |
| Intelligent condition assessment of power transformers A Peimankar University of Canterbury, 2017 | 3 | 2017 |
| A collection of multiregistry data on patients at high risk of lung cancer—a Danish retrospective cohort study of nearly 40,000 patients MB Henriksen, TF Hansen, LH Jensen, CL Brasen, A Peimankar, ... Translational Lung Cancer Research 12 (12), 2392, 2023 | 2 | 2023 |
| Correlation between electrical measured partial discharge and acoustic emission signals from new and thermal aged pressboards in oil SAM Najafi, A Peimankar, E Gockenbach, H Borsi 18th International Symposium on High Voltage Engineering (ISH2013), 810-814, 2013 | 2 | 2013 |
| AUD-DSS: a decision support system for early detection of patients with alcohol use disorder A Ebrahimi, UK Wiil, R Baskaran, A Peimankar, K Andersen, AS Nielsen BMC bioinformatics 24 (1), 329, 2023 | 1 | 2023 |
| Pulmonologists-Level lung cancer detection based on standard blood test results and smoking status using an explainable machine learning approach RNH Flyckt, L Sjodsholm, MHB Henriksen, CL Brasen, A Ebrahimi, ... arXiv preprint arXiv:2402.09596, 2024 | | 2024 |
| Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks M Vibæk, A Peimankar, UK Wiil, D Arvidsson, JC Brønd Sensors 24 (8), 2520, 2024 | | 2024 |
Sadasivan PuthusserypadyTechnical University of DenmarkVerified email at dtu.dk
