An Iterative Analysis of Deep Learning Models Including LSTM and CNN-GRU for Real-Time Seizure Prediction Ramula Uttham Sai, Latha Parthiban 2nd International Conference on Machine Learning and Autonomous Systems Icmlas 2025 Proceedings, 2025 Epilepsy is the most common of all neurological conditions, affecting over 50 million people in the global population. Timely prediction of seizures may reduce mortality rates and improve outcomes for affected patients. The existing seizure detection and prediction methodologies rely on machine learning algorithms that need handcrafted features, have poor adaptability to EEG signals, and inadequate generalization capability. Additionally, past reviews have primarily focused on isolated aspects of seizure prediction and not on the comprehensive evaluation of the advancement in DL models along with their integration with the emergent technologies like IoT and transfer learning. The current review bridges this gap by providing an empirical analysis of 15 state-of-the-art DL methodologies for real-time seizure prediction. Some techniques addressed include LSTM, CNN-GRU-AM-based models because they can extract spatiotemporal features automatically and hybrid optimization frameworks such as WCA-PSO-EELM that result in more accurate classifications. New ideas include adaptation for concept drift and transfer learning for adaptability to different patients and lower computations. The review is made on multimodal approaches by integrating EEG and MRI data with IoMT applications for remote monitoring regarding the aspects of accessibility and cost-effectiveness of healthcare. This work is presented, reporting that models such as CNN-GRU-AM and WCA-PSO-EELM offer superior accuracy (>99%) and specificity, while the transfer learning approach proves to be a robust solution to data-scarce scenarios. This review provides a roadmap for future research and clinical deployment by systematically comparing these methods using performance metrics. The results are of significant relevance for personalized medicine, advancing real-time monitoring systems, and developing AI-driven innovations in neurological healthcare sets.
Uncertainty-Aware AI for Enhanced Chronic Kidney Disease Diagnosis: A Review of Explainable and Reliable Models Bellamgubba Anoch, Latha Parthiban International Conference on Computational Robotics Testing and Engineering Evaluation Iccrtee 2025, 2025 Chronic kidney disease is a progressive condition affecting millions globally, often progressing to end-stage renal disease without early detection and management. Traditional diagnostic methods, relying on serum biomarkers and manual image interpretation, can be time-consuming, subjective, and variable. Artificial intelligence, particularly deep learning, has emerged as a transformative tool, automating CKD detection, classification, and risk prediction using medical imaging modalities like ultrasound, CT, and MRI. This review comprehensively examines AI-driven CKD diagnosis, focusing on deep learning-based image analysis, segmentation techniques, classification models, and uncertainty quantification methods. We explore various architectures, including CNNs, U-Net, Vision Transformers, and hybrid AI models, highlighting their effectiveness in automating kidney segmentation and CKD severity classification. We also discuss uncertainty-aware AI models, emphasizing the importance of model reliability and interpretability for clinical deployment. Despite advancements, challenges remain, including limited annotated datasets, model generalization issues, interpretability concerns, domain shifts, and ethical considerations. Future research should prioritize developing large-scale multi-institutional datasets, integrating multi-modal AI approaches, enhancing explainability through interpretable AI models, and establishing standardized regulatory frameworks for AI-driven CKD diagnosis
An Empirical Study of Quantum Machine Learning for Early Glaucoma Detection Using Retinal Fundus Images T Mahesh, Latha Parthiban International Conference on Emerging Trends in Engineering and Technology Icetet, 2025 Glaucoma is a condition of the eye that leads to permanent vision loss during progression of the disease to the advanced stage. This happens owing to unsuitable intraocular pressure inside an eye, resulting in impairment of the optic nerve. The glaucoma does not reveal any symptoms in its very preliminary stage. Therefore, it is significant to detect this disease earlier to prevent blindness. Fundus image is expansively employed by the ophthalmologists to assist in diagnosing glaucoma. However, manually inspecting the obtained fundus images is highly prone to inter-observer variation. Hence, an effective method is necessary for making a reliable, accurate and quick diagnosis of glaucoma regarding optic nerve features of the fundus images. In this research, various conventional techniques are reviewed by categorizing those methods into Quantum Machine Learning (QML)-based, Deep Learning (DL)-based, Machine Learning (ML)-based, ensemble learning-based and optimization-based methods. Moreover, analysis is accomplished based on toolsets, evaluation metrics, publication year and datasets. Additionally, research gaps of classical methods are described. From the analysis performed, QML-based methods are mostly utilized. Also, commonly employed toolsets and datasets are PYTHON and High-Resolution Fundus (HRF). Moreover, most of the papers for glaucoma detection are published in 2024, and the widely considered evaluation metric is accuracy.
Efficient quantum-based secure route creation and data transfer in mobile ad-hoc networks using multi-user co-operative motion mechanism Frontiers in Quantum Computing New Research, 2022
Quantum-based deep learning for multi-level grading of mangoes Frontiers in Quantum Computing New Research, 2022
Medical data analytics for secure multi-party-primarily based cloud computing utilizing homomorphic encryption Journal of Scientific and Industrial Research, 2021
Emotion detection in IoT-based E-Learning using convolution neural network Fuzzy Intelligent Systems Methodologies Techniques and Applications, 2021
Design of computationally intelligent decision support system using data analytics A Closer Look at Big Data Analytics, 2021
Data analytics using computationally intelligent agents for medical diagnosis A Closer Look at Big Data Analytics, 2021
Deep neural networks in bioinformatics for motif identification A Closer Look at Big Data Analytics, 2021
Utilizing scratch to create computational thinking at school with artificial intelligence A Closer Look at Big Data Analytics, 2021
Tracking system for birds migration using sensors A Closer Look at Big Data Analytics, 2021
An optimal deep neural network model for lymph disease identification and classification International Journal of Scientific and Technology Research, 2020
Energy efficient traffic protocol in wireless sensor networks using improved metaheuristic algorithm International Journal of Pharmaceutical Research, 2019
Improved energy efficient light weighted dynamic routing protocol in wireless sensor networks International Journal of Pharmaceutical Research, 2019
An experimental technique on features extraction for product feedback using opinion mining International Journal of Innovative Technology and Exploring Engineering, 2019
Cancer prediction with gene expression data G Sivagamasundari, Latha Parthiban, Anirban Mukhopadhyay, I Balasundar, Evgeniy Raju, et al. International Journal of Recent Technology and Engineering, 2019
An experimental analysis on opinion mining feature identification for product analysis International Journal of Innovative Technology and Exploring Engineering, 2019
An improved location based routing protocol for WSN using novel location proximity algorithm International Journal of Recent Technology and Engineering, 2019
Opinion mining of product features with customer International Journal of Recent Technology and Engineering, 2019
Opinion mining on amazon product data using dictionary approach International Journal of Recent Technology and Engineering, 2019
Opinion mining on product data using modified SVM Journal of Advanced Research in Dynamical and Control Systems, 2019
A Dynamic DNA for Key-based Cryptography Bahubali Akiwate, Latha Parthiban Proceedings of the International Conference on Computational Techniques Electronics and Mechanical Systems Ctems 2018, 2018
Efficient wireless sensor network with enhanced-omra routing algorithm with low OFDM papr International Journal of Civil Engineering and Technology, 2018
Opinion mining of amazon product data by hybrid svm Journal of Advanced Research in Dynamical and Control Systems, 2018
Staff ranking system on the basis of student knowledge, academic result and feedback Journal of Advanced Research in Dynamical and Control Systems, 2018
A novel privacy preserving visual cryptography based scheme for telemedicine applications Biomedical Research India, 2018
Comparative study of routing techniques in Wireless Sensor Network Al-Shafiq Bin Abdul Wahid, Mohd Zamani Bin Ahmad, Sunarsih ., Mohd Najib Bin Abdul Ghani Yolhamid, Mohamad Abu Ubaidah Amir Abu Zarim, Aisha Binti Abdullah, Nur Hanani Bt Ahmad Azlan International Journal of Engineering and Technology Uae, 2018
Auditing of data integrity over dynamic data in cloud P. Santhosh Kumar, Latha Parthiban, V. Jegatheeswari Proceedings 2017 2nd International Conference on Recent Trends and Challenges in Computational Models Icrtccm 2017, 2017
Improved energy efficient multi-hop WSN using novel routing mechanism with hull convex function Journal of Advanced Research in Dynamical and Control Systems, 2017
Abnormality detection using weighed Particle Swarm Optimization and Smooth Support Vector machine Biomedical Research India, 2017
Medical image segmentation with fuzzy C-means and kernelized fuzzy C-means hybridized on PSO and QPSO International Arab Journal of Information Technology, 2017
Design of distributed model predictive control using particle swarm optimization for alkylation process Journal of Chemical and Pharmaceutical Sciences, 2016
Data mining techniques for finding serious Adverse Events Journal of Chemical and Pharmaceutical Sciences, 2016
A novel approach for E-learning using QPSO algorithm International Journal of Control Theory and Applications, 2016
Evaluation and personalization of noise reduction algorithms in digital hearing AIDS Journal of Chemical and Pharmaceutical Sciences, 2016
Diagnosis of abnormality in ultrasound kidney images using spectral components Journal of Chemical and Pharmaceutical Sciences, 2016
FCM-FCS: Hybridization of fractional cuckoo search with FCM for high dimensional data clustering process International Review on Computers and Software, 2013
ROI detection and segmentation of medical images using optimized thresholding and clustering International Journal of Pharma and Bio Sciences, 2013
MRI image denoising for telemedicine L. Parthiban, R. Subramanian Healthcom 2006 Mobile E Health for Developing Countries 2006 8th International Conference on E Health Networking Applications and Services, 2006
RECENT SCHOLAR PUBLICATIONS
Federated Learning for Real-Time Disease Prediction: A Scalable Framework for Personalized Healthcare in Internet of Things-Enabled Environment K Balamurugan, TP Latchoumi, L Parthiban, A Venkateswara, ... Federated Learning for Healthcare, 259-276 , 2026 2026
Analysis of variable-order fractional enzyme kinetics model with time delay: A. K et al. K Agilan, S Naveen, S Suganya, V Parthiban Scientific Reports 15 (1), 34255 , 2025 2025 Citations: 1
Detection and classification of medical images using deep learning for chronic kidney disease B Anoch, L Parthiban International Urology and Nephrology, 1-22 , 2025 2025 Citations: 3
The vital role of nurses in promoting oral health care L Parthiban Moorthy, M Rezaei, G Sasan Journal of Nursing Advances in Clinical Sciences 3 (1), 67-68 , 2025 2025 Citations: 1
Optimal control analysis of fractional order delayed SIQR model for COVID-19 S Suganya, V Parthiban The European Physical Journal Special Topics 234 (8), 1809-1821 , 2025 2025 Citations: 4
An Empirical Study of Quantum Machine Learning for Early Glaucoma Detection Using Retinal Fundus Images T Mahesh, L Parthiban 2025 12th International Conference on Emerging Trends in Engineering … , 2025 2025 Citations: 1
Comparative analysis of random forest classification over linear regression classifier to detect cyber thefts in credit card to reduce false rate KR Ruthvik, GCP Latha AIP Conference Proceedings 3300 (1), 020198 , 2025 2025
Uncertainty-aware AI for enhanced chronic kidney disease diagnosis: a review of explainable and reliable models B Anoch, L Parthiban 2025 International Conference on Computational Robotics, Testing and … , 2025 2025 Citations: 6
An Iterative Analysis of Deep Learning Models Including LSTM and CNN-GRU for Real-Time Seizure Prediction RU Sai, L Parthiban 2025 International Conference on Machine Learning and Autonomous Systems … , 2025 2025
Improved Support Vector Machine for ECG Signal Classification in Implantable Biomedical Devices PSSR Patchamatla, ZA Balsem, KG Parthiban, R AC 2025 3rd International Conference on Integrated Circuits and Communication … , 2025 2025 Citations: 6
Integrating Blockchain in Healthcare to Secure Data L Parthiban, B Hariharan, R Parthiban Blockchain and IoT, 154-176 , 2025 2025
Utilizing Blockchain and Interplanetary File System for Enhanced User Privacy in Secure Data Sharing K Balamurugan, M Azhagiri, PAH Vardhini, E Jijo, L Parthiban Blockchain and IoT, 42-60 , 2025 2025 Citations: 1
Optimizing Tuberculosis Detection Through DenseNet Architecture and Ensemble Learning Techniques J Thirunavukkarasu, R Charumathi, M Parthiban, V Pavithra, ... 2024 International Conference on Innovative Computing, Intelligent … , 2024 2024 Citations: 1
Normalized group activations based feature extraction technique using heterogeneous data for Alzheimer’s disease classification K Vaithianathan, JB Pernabas, L Parthiban, M Rashid, SS Alshamrani PeerJ Computer Science 10, e2502 , 2024 2024 Citations: 1
Empowering rural micro-entrepreneurs through technoficing: A process model for mobilizing and developing indigenous knowledge R Parthiban, R Sun, I Qureshi, S Bandyopadhyay The Journal of Strategic Information Systems 33 (2), 101836 , 2024 2024 Citations: 46
Automatic liver segmentation using U-Net deep learning architecture for additive manufacturing J Giri, T Sathish, T Sheikh, N Sunheriya, P Giri, R Chadge, C Mahatme, ... Interactions 245 (1), 90 , 2024 2024 Citations: 34
Integrating Blockchain and Artificial Intelligence for Industry 4.0 Innovations S Goundar, R Anandan Springer , 2024 2024 Citations: 9
A review of different techniques used for routing in wireless sensor networks DT Anandrao, L Parthiban International Journal of Advanced Intelligence Paradigms 28 (3-4), 316-326 , 2024 2024 Citations: 1
An effective content based image retrieval system using deep learning based inception model E Ranjith, L Parthiban, TP Latchoumi, SA Kumar, DG Perera, ... Wireless Personal Communications 133 (2), 811-829 , 2023 2023 Citations: 21
Kryptoverse: A Fully-Fledged Cryptocurrency Transfer Website Based on Web 3.0 K Pazhanisamy, L Parthiban, R Kannadasan, AS Anakath, R Parthiban Integrating Blockchain and Artificial Intelligence for Industry 4.0 … , 2023 2023
MOST CITED SCHOLAR PUBLICATIONS
Intelligent heart disease prediction system using CANFIS and genetic algorithm L Parthiban, R Subramanian International Journal of Biological, Biomedical and Medical Sciences 3 (3 … , 2008 2008 Citations: 356
Applying machine learning methods in diagnosing heart disease for diabetic patients G Parthiban, SK Srivatsa International Journal of Applied Information Systems 3 (7), 25-30 , 2012 2012 Citations: 253
Maximizing the wireless sensor networks lifetime through energy efficient connected coverage J Roselin, P Latha, S Benitta Ad Hoc Networks 62, 1-10 , 2017 2017 Citations: 163
Quasi oppositional dragonfly algorithm for load balancing in cloud computing environment TP Latchoumi, L Parthiban Wireless Personal Communications 122 (3), 2639-2656 , 2022 2022 Citations: 155
Diagnosis of heart disease for diabetic patients using naive bayes method G Parthiban, A Rajesh, SK Srivatsa International Journal of Computer Applications 24 (3), 7-11 , 2011 2011 Citations: 130
Face recognition using neural networks P Latha, L Ganesan, S Annadurai Signal Processing: An International Journal (SPIJ) 3 (5), 153-160 , 2009 2009 Citations: 123
Applying machine learning techniques for predicting the risk of chronic kidney disease KRA Padmanaban, G Parthiban Indian Journal of Science and Technology 9 (29), 1-6 , 2016 2016 Citations: 120
Phenotyping crop plants for physiological and biochemical traits P Sudhakar, P Latha, PV Reddy Academic Press , 2016 2016 Citations: 110
A review on cleaner strategies for extraction of chitosan and its application in toxic pollutant removal M Abhinaya, R Parthiban, PS Kumar, DVN Vo Environmental research 196, 110996 , 2021 2021 Citations: 108
Predicting individual learning performance using machine‐learning hybridized with the teaching‐learning‐based optimization M Arashpour, EM Golafshani, R Parthiban, J Lamborn, A Kashani, H Li, ... Computer Applications in Engineering Education 31 (1), 83-99 , 2023 2023 Citations: 102
Digitally mediated value creation for non-commodity base of the pyramid producers R Parthiban, I Qureshi, S Bandyopadhyay, S Jaikumar International Journal of Information Management 56, 102256 , 2021 2021 Citations: 97
A novel texture extraction technique with T1 weighted MRI for the classification of Alzheimer’s disease K Vaithinathan, L Parthiban, Alzheimer's Disease Neuroimaging Initiative Journal of neuroscience methods 318, 84-99 , 2019 2019 Citations: 94
A multi criteria decision making approach for suppliers selection P Parthiban, HA Zubar, CP Garge Procedia Engineering 38, 2312-2328 , 2012 2012 Citations: 90
The effect of cybercrime on a Bank’s finances AR Raghavan, L Parthiban International Journal of Current Research & Academic Review 2 (2), 173-178 , 2014 2014 Citations: 89
Classification of diseased plant leaves using neural network algorithms K Muthukannan, P Latha, RP Selvi, P Nisha ARPN Journal of Engineering and Applied Sciences 10 (4), 1913-1919 , 2015 2015 Citations: 88
Hyperledger blockchain enabled secure medical record management with deep learning-based diagnosis model N Sammeta, L Parthiban Complex & Intelligent Systems 8 (1), 625-640 , 2022 2022 Citations: 85
A neural network approach for traffic prediction and routing with missing data imputation for intelligent transportation system RKC Chan, JMY Lim, R Parthiban Expert Systems with Applications 171, 114573 , 2021 2021 Citations: 78
Analyzing the security mechanisms to prevent unauthorized access in cloud and network security K Maithili, V Vinothkumar, P Latha Journal of Computational and Theoretical Nanoscience 15 (6-7), 2059-2063 , 2018 2018 Citations: 76
Abnormality detection using weighed particle swarm optimization and smooth support vector machine TP Latchoumi, L Parthiban Biomedical Research 28 (11), 4749-4751 , 2017 2017 Citations: 73
Trusted framework for online banking in public cloud using multi-factor authentication and privacy protection gateway S Nagaraju, L Parthiban Journal of Cloud Computing 4 (1), 22 , 2015 2015 Citations: 71