B. Dhananjay, P. K. Rajnala, B. C. Neelapu, K. Pal, and S.,"A Q-transform-based deep learning model for the classification of atrial fibrillation types", Physical and Engineering Sciences in Medicine, Springer, February 2024, 10.1007/s13246-024-01391-3       Article

P. V. N, P. Kumar, B. C. Neelapu, K. Pal, and S.,"Can atrial lead system ameliorate the diagnosis of atrial arrhythmias?", Medical Hypotheses, Elsevier, March 2024, 10.1016/j.mehy.2024.111280       Article

B. Dhananjay, B. C. Neelapu, K. Pal, and S.,"Stacked machine learning models to classify atrial disorders based on clinical ECG features: a method to predict early atrial fibrillation", Biomedical Engineering/Biomedizinische Technik, De Gruyter, March 2023, 10.1515/bmt-2022-0430       Article

B. K. Pradhan, B. C. Neelapu, S., D. Kim, and K. Pal,"A review on the applications of time-frequency methods in ECG analysis", Journal of Healthcare Engineering, Hindawi, February 2023, 10.1155/2023/3145483       Article

A. Zaffar, N. K, N. Nagaraj, S., and B. P,"Optimization and kinetic modeling of phosphate recovery as struvite by electrocoagulation from source-separated urine", Environmental Science and Pollution Research, vol.30, pp.20721–20735, Springer, January 2023, 10.1007/s11356-022-23446-2       Article

S. Karimulla, A. Bhardwaj, V. Sangareddi, and S.,"New corrected QT formula optimal for different heart rates: A comparative study", Biomedical Engineering: Applications, Basis and Communications, vol.35, no.1, pp.2250043, World Scientific Publishing, February 2023, 10.4015/S1016237222500430       Article

B. Dey, B. Behera, A. K. R, S., and B. P,"Functionalized bacterial cellulose-based biopolymers for biomedical applications", Biotic Resources: Circular Bioeconomy Perspective, ch.8, pp.175-192, CRC Press, February 2023, 10.1201/9781003335740-8       Inbook

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