Pyingkodi, M., Shanthi, S., Muthukumaran, M., Nanthini, K., & Thenmozhi, K. (2020). Hybrid bee colony and weighted ranking firefly optimization for cancer detection from gene regulatory sequences. International Journal of Scientific & Technology Research, 9(01). (Journal- Scopus)

Pyingkodi M, Shanthi S, Thenmozhi K, Hemalatha D & Nanthini K. A novel deep learning method for identification of cancer genes from gene expression dataset. Machine Learning and Deep Learning in Real-Time Applications, Vol. 9, 2020, pp.129-144. (Book Chapter – Scopus)

Dhivya M, Pyingkodi M, Shanthi S, Saravanan T.M, Thenmozhi K, Nanthini K, Hemalatha D & Muthukumaran M. Performance Study of Classification Algorithms Using the Microarray Breast Cancer Dataset. International Journal of Future Generation Communication and Networking, 13(2), 2020. (Journal – Scopus)

Pyingkodi, M., Thenmozhi, K., Karthikeyan, M., Nanthini, K., Martin, A. A., Deepak, P. V., & Jegan, K. (2022, March). IoT technologies for precision agriculture: a survey. In 2022 6th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 372-376). IEEE. (Conference-Scopus)

Pyingkodi, M., Thenmozhi, K., Nanthini, K., Karthikeyan, M., Palarimath, S., Erajavignesh, V., & Kumar, G. B. A. (2022, January). Sensor based smart agriculture with IoT technologies: a review. In 2022 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1-7). IEEE. (Conference-Scopus)

Nanthini, K., Pyingkodi, M., & Sivabalaselvamani, D. (2022, August). EEG Signal Analysis for Emotional Classification. In 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 192-198). (Conference-Scopus)

Nanthini, K., Pyingkodi, M., Sivabalaselvamani, D., Kumari, S., & Kumar, T. (2022). Performance analysis of machine learning algorithms in Heart diseases prediction. In IoT Based Control Networks and Intelligent Systems: Proceedings of 3rd ICICNIS 2022 (pp. 407-423). Singapore: Springer Nature Singapore. (Conference-Scopus)

Pyingkodi, M., Thenmozhi, K., Nanthini, K., Karthikeyan, M., Kalpana, T., & Deepak, P. V. (2023). Examination of Water Impurities Using IoT and Machine Learning Techniques. In IoT Based Control Networks and Intelligent Systems (pp. 675-687). Springer, Singapore. (Conference-Scopus)

Nanthini, K., Sivabalaselvamani, D., Chitra, K., Gokul, P., KavinKumar, S., & Kishore, S. (2023, February). A Survey on Data Augmentation Techniques. In 2023 7th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 913-920). IEEE. (Conference-Scopus)

Nanthini, K., Sivabalaselvamani, D., Selvakarthi, D., Pavethran, D., Srinaath, N., & Vignesh, K. S. (2023, March). Performance of Recurrent Neural Networks in Liver Disease Classification. In 2023 Second International Conference on Electronics and Renewable Systems (ICEARS) (pp. 1491-1497). IEEE. (Conference-Scopus)

Nanthini, K., Sivabalaselvamani, D., Chitra, K., Mohideen, P. A., & Raja, R. D. (2023, March). Cardiac Arrhythmia Detection and Prediction Using Deep Learning Technique. In Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems: ICCCES 2022 (pp. 983-1003). Singapore: Springer Nature Singapore. (Conference-Scopus)

Nanthini, K., Sivabalaselvamani, D., Sharvanthika, K. S., Ojha, S. K., & Siva, M. (2023, December). Diabetic Retinopathy Detection using Squeezenet. In 2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS) (pp. 695-701). IEEE. (Conference-Scopus)

Sivabalaselvamani, D., Rahunathan, L., Nanthini, K., Harshini, T., & Hariprasath, C. (2023, August). Soil classification using deep learning techniques. In 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) (pp. 582-586). IEEE. (Conference-Scopus)

Sivabalaselvamani, D., Nanthini, K., Selvakarthi, D., Niranchan, V. M., Kumar, L. S., & Swetha, P. (2023, September). Skin melanoma detection using image augmentation. In 2023 4th International Conference on Smart Electronics and Communication (ICOSEC) (pp. 1624-1630). IEEE. (Conference-Scopus)

Chitra, K., Tamilarasi, A., Pyingkodi, M., Nanthini, K., Sneka, V., Swetha, S., & Vishalini, P. (2023, January). Animals detection system in the farm area using IoT. In 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1-6). IEEE. (Conference-Scopus)

Nanthini, K., Tamilarasi, A., Sivabalaselvamani, D., Harini, V. S., Janaki, R., & Madhan, V. K. (2024). EEG signal classification using 1D-CNN and BILSTM. In Artificial Intelligence, Blockchain, Computing and Security Volume 2 (pp. 453-457). CRC Press. (Book Chapter – Scopus)

Sivabalaselvamani, D., Nanthini, K., Vanithamani, S., & Nivetha, L. (2023). Performance of deep learning approaches for detection and classification of ceramic tile defects. Journal of Ceramic Processing Research, 24(1), 78-88. (SCI)

Sivabalaselvamani, D., Nanthini, K., Nagaraj, B. K., Kannan, K. G., Hariharan, K., & Mallingeshwaran, M. (2024). Healthcare Monitoring and Analysis Using ThingSpeak IoT Platform: Capturing and Analyzing Sensor Data for Enhanced Patient Care. In Advanced Applications in Osmotic Computing (pp. 126-150). IGI Global. (Book Chapter – Scopus)

Nanthini K., Tamilarasi A., Sivabalaselvamani D., & Suresh, P. Automated classification of Alzheimer’s disease based on deep belief neural networks. Neural Computing and Applications, 2024, vol. 36, pp.1-15. (SCI)

Nanthini K., Sivabalaselvamani D., MC Madhan Kumar, & R Kaviya. (2024). Comprehensive EEG Signal Feature Extraction for Neurological Disorder Diagnosis: Focus on Alzheimer’s, Parkinson’s, and Seizure Disorders. International Research Journal of Multidisciplinary Technovation, 6(5), 80-93. (Journal-Scopus)