A. Bhardwaj, B. Dhananjay, P. V. N, D. Chowdhury, R. P. Kumar, K. Pal, S., and B. C. Neelapu,"A holistic overview of artificial intelligence in detection, classification and prediction of atrial fibrillation using electrocardiogram: a systematic review and meta-analysis", Archives of Computational Methods in Engineering, Springer, April 2023, 10.1007/s11831-023-09935-8       Article

D. Chowdhury, B. C. Neelapu, K. Pal, and S.,"Machine learning-based classification of ischemic and non-ischemic exercise stress test ECG", in Computing in Cardiology 2022, vol.49, IEEE, March 2023, 10.22489/CinC.2022.276       Inproceedings

R. Bandyopadhyay, B. C. Neelapu, K. Pal, and S.,"Examining R peak changes in ischemic condition using random forest classifier under stress test ECG", in 10th International Conference on Signal Processing and Integrated Networks (SPIN), pp.82-86, IEEE, Noida, India, May 2023, 10.1109/SPIN57001.2023.10117129       Inproceedings

A. Zaffar, N. K, C. Sahoo, S., and B. P,"Process feasibility and sustainability of struvite crystallization from wastewater through electrocoagulation", Microconstituents in the Environment: Occurrence, Fate, Removal and Management, ch.11, pp.247-271, John Wiley & Sons, May 2023, 10.1002/9781119825289.ch11       Inbook

B. Dey, N. K, R. Chaudhuri, A. Zaffar, S., and B. P,"Engineering perspectives on the application of photosynthetic algal microbial fuel cells for simultaneous wastewater remediation and bioelectricity generation", Waste to Profit: Environmental Concerns and Sustainable Development, ch.8, pp.103-119, CRC Press, June 2023       Inbook

N. P. Venkatesh, R. P. Kumar, B. C. Neelapu, K. Pal, and S.,"CatBoost-based improved detection of P-wave changes in sinus rhythm and tachycardia conditions: a lead selection study", Physical and Engineering Sciences in Medicine, vol.46, pp.925-944, Springer, May 2023, 10.1007/s13246-023-01274-z       Article

R. Bandyopadhyay, B. C. Neelapu, K. Pal, and S.,"Examining R Peak Changes in Ischemic Condition using Random Forest Classifier under Stress Test ECG", in 2023 10th International Conference on Signal Processing and Integrated Networks, pp.82-86, IEEE, The most common clinical criteria for electrocardiographic diagnosis of myocardial ischemia include ST segment changes but not the QRS morphology. This study aimed to interpret the variations in the amplitude of the R wave that might be helpful in better diagnosis of ischemia during stress testing a, March 2023, 10.1109/SPIN57001.2023.10117129.       Inproceedings

S. K. Nayak, B. K. Pradhan, B. Mohanty, S., S. S. Ray, J. Wawrzyniak, M. Jarzebski, and K. Pal,"A Review of Methods and Applications for a Heart Rate Variability Analysis", Algorithms, vol.16, no.433, MDPI 2023, 10.3390/a16090433       Article

P. V. N, R. P. Kumar, B. C. Neelapu, K. Pal, and S.,"Atrial features-based prediction of sinus tachycardia using LSTM-RNN model", in Computing in Cardiology, IEEE, December 2023, 10.22489/CinC.2023.163       Inproceedings

P. V. N, P. Kumar, B. C. Neelapu, K. Pal, and S.,"Atrial features-based prediction of sinus tachycardia using LSTM-RNN model", in Computing in Cardiology, IEEE, December 2023, 10.22489/CinC.2023.163       Inproceedings