Segmentation and analysis of brain subcortical regions using regularized multiphase level set in autistic MR images. - Agastinose Ronickom Jac Fredo; G. Kavitha; S. Ramakrishnan 001 (Int. J. Imaging Syst. Technol., 2014)

Modified-MaMeMi filter bank for efficient extraction of brainwaves from electroencephalograms. - Rakshit Mittal; A. Amalin Prince; Saif Nalband; Femi Robert; Agastinose Ronickom Jac Fredo (Biomed. Signal Process. Control., 2021)

Performance of machine learning classification models of autism using resting-state fMRI is contingent on sample heterogeneity. - Maya A. Reiter; Afrooz Jahedi; Agastinose Ronickom Jac Fredo; Inna Fishman; Barbara A. Bailey; Ralph-Axel Müller (Neural Comput. Appl., 2021)

Low-Power Hardware Accelerator for Detrending Measured Biopotential Data. - Rakshit Mittal; A. Amalin Prince; Saif Nalband; Femi Robert; Agastinose Ronickom Jac Fredo (IEEE Trans. Instrum. Meas., 2021)

Automated Diagnosis of Autism Spectrum Disorder Condition Using Shape Based Features Extracted from Brainstem. - Vaibhav Jain; Abirami Selvaraj; Rakshit Mittal; Priya Rani; Anandh Kilpattu Ramaniharan; Jac Fredo Agastinose Ronickom (MIE, 2022)

Study on the effect of extreme learning machine and its variants in differentiating Alzheimer conditions from selective regions of brain MR images. - Sreelakshmi Shaji; Jac Fredo Agastinose Ronickom; Anandh Kilpattu Ramaniharan; Ramakrishnan Swaminathan (Expert Syst. Appl., 2022)

Time-Sliced Architecture for Efficient Accelerator to Detrend High-Definition Electroencephalograms. - Rakshit Mittal; A. Amalin Prince; Agastinose Ronickom Jac Fredo (IEEE Trans. Instrum. Meas., 2022)

A Framework to Diagnose Autism Spectrum Disorder Using Morphological Connectivity of sMRI and XGBoost. - Vaibhavi Gupta; Gokul Manoj; Aditi Bhattacharya; Sandeep Singh Sengar; Rakesh Mishra; Bhoomika R. Kar; Chhitij Srivastava; Jac Fredo Agastinose Ronickom (EFMI-STC, 2023)

Age-Specific Diagnostic Classification of ASD Using Deep Learning Approaches. - Vaibhav Jain; Sandeep Singh Sengar; Jac Fredo Agastinose Ronickom (EFMI-STC, 2023)

Deep Learning Framework for Categorical Emotional States Assessment Using Electrodermal Activity Signals. - Praveen Kumar Govarthan; Nagarajan Sriram Kumar Pa Ganapathy; Jac Fredo Agastinose Ronickom (ICIMTH, 2023)

Identifying the Optimal Location of Facial EMG for Emotion Detection Using Logistic Regression. - Praveen Kumar Sriram Kumar Pa Govarthan; Swarubini PJ; Mythili Aasaithambi; Nagarajan Ganapathy; Karthik P. A.; Deepesh Kumar; Jac Fredo Agastinose Ronickom (ICIMTH, 2023)

Automated Emotion Recognition System Using Blood Volume Pulse and XGBoost Learning. - Lokesh Naidu Lebaka; Praveen Kumar Sriram Kumar Pa Govarthan; Priya Rani; Nagarajan Ganapathy; Jac Fredo Agastinose Ronickom (ICIMTH, 2023)

Diagnostic Classification of ASD Using Fractal Functional Connectivity of fMRI and Logistic Regression. - Chetan Rakshe; Suja Kunneth; Soumya Sundaram; Jac Fredo Agastinose Ronickom (ICIMTH, 2023)

Diagnostic Classification of ASD Improves with Structural Connectivity of DTI and Logistic Regression. - Ravi Ratnaik; Chetan Rakshe; Manoj Kumar; Jac Fredo Agastinose Ronickom (ICIMTH, 2023)

Multi-Class Seizure Type Classification Using Features Extracted from the EEG. - Abirami Selvaraj; Swarubini PJ; John Thomas; Yuvaraj Rajamanickam; Ramshekhar N. Menon; Jac Fredo Agastinose Ronickom (ICIMTH, 2023)

Optimization of Pre-Ictal Interval Time Period for Epileptic Seizure Prediction Using Temporal and Frequency Features. - Abdul Aleem Shaik Gadda; Dhanvi Vedantham; John Thomas; Yuvaraj Rajamanickam; Ramshekhar N. Menon; Jac Fredo Agastinose Ronickom (MIE, 2023)

Comparative Analysis of Electrodermal Activity Decomposition Methods in Emotion Detection Using Machine Learning. - Sriram Kumar P; Praveen Kumar Govarthan; Nagarajan Ganapathy; Jac Fredo Agastinose Ronickom (MIE, 2023)

Differential Gene Expression Data Analysis of ASD Using Random Forest. - Praveen Kumar Pragyaa Govarthan; Kshitij Sinha; Sudip Mukherjee; Jac Fredo Agastinose Ronickom (MIE, 2023)

Low Valence Low Arousal Stimuli: An Effective Candidate for EEG-Based Biometrics Authentication System. - Jahanvi Jeswani; Praveen Kumar Govarthan; Abirami Selvaraj; A. Amalin Prince; John Thomas; Mohanavelu Kalathe; Venkat Sreeraj V. Se Subramaniam; Jac Fredo Agastinose Ronickom (MIE, 2023)

Age-Stratified Differences in Morphological Connectivity Patterns in ASD: An sMRI and Machine Learning Approach. - Gokul Manoj; Sandeep Singh Sengar; Jac Fredo Agastinose Ronickom (CoRR, 2023)

Automated Multi-Class Seizure-Type Classification System Using EEG Signals and Machine Learning Algorithms. - Abirami Selvaraj; Tikaram; M. Kathiravan; Yuvaraj Rajamanickam; Ramshekhar N. Menon; John Thomas; Periyamolapalayam Allimuthu Karthick; A. Amalin Prince; Jac Fredo Agastinose Ronickom (IEEE Access, 2024)

Emotion classification using electrocardiogram and machine learning: A study on the effect of windowing techniques. - Praveen Kumar Govarthan; Sriram Kumar P; Nagarajan Ganapathy; Jac Fredo Agastinose Ronickom (Expert Syst. Appl., 2024)

Deep Learning-Based Automated Emotion Recognition Using Multimodal Physiological Signals and Time-Frequency Methods. - Sriram Kumar P; Praveen Kumar Govarthan; Abdul Aleem Shaik Gadda; Nagarajan Ganapathy; Jac Fredo Agastinose Ronickom (IEEE Trans. Instrum. Meas., 2024)

Optimal Electrodermal Activity Segment for Enhanced Emotion Recognition Using Spectrogram-Based Feature Extraction and Machine Learning. - Sriram Kumar P; Jac Fredo Agastinose Ronickom (Int. J. Neural Syst., 2024)

Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods. - Chetan Rakshe; Suja Kunneth; Soumya Sundaram; Murugappan Murugappan; Jac Fredo Agastinose Ronickom (Neural Comput. Appl., 2024)

Correction: Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods. - Chetan Rakshe; Suja Kunneth; Soumya Sundaram; Murugappan Murugappan; Jac Fredo Agastinose Ronickom (Neural Comput. Appl., 2024)

Binding Affinity Prediction for Pancreatic Ductal Adenocarcinoma Using Drug-Target Descriptors and Artificial Intelligence. - Pragya; A. Amalin Prince; Jac Fredo Agastinose Ronickom (IEEE Access, 2025)

Fine-Tuning EEG Channel Utilization for Emotionally Stimulated Biometric Authentication. - Chetan Rakshe; Christy Bobby Thomas; Mohanavelu Kalathe; Vanteemar S. Sreeraj; Ganesan Venkatasubramanian; Deepesh Kumar; A. Amalin Prince; Jac Fredo Agastinose Ronickom (IEEE Access, 2025)

Evaluating the effectiveness of machine learning in identifying the optimal facial electromyography location for emotion detection. - Vinay Kumar Barigala; Swarubini PJ; Sriram Kumar P; Nagarajan Ganapathy; Karthik P. A.; Deepesh Kumar; Jac Fredo Agastinose Ronickom (Biomed. Signal Process. Control., 2025)

Emotion Classification Through Optimal Segments of EDA and Texture Analysis of Time-Encoded Images With Artificial Intelligence. - Sriram Kumar P; Jac Fredo Agastinose Ronickom (IEEE Trans. Instrum. Meas., 2025)

Diagnostic classification of autism spectrum disorder using sMRI improves with the morphological distance-related features compared to morphological features. - Gokul Manoj; Vaibhavi Gupta; Aditi Bhattacharya; Abdul Aleem Shaik Gadda; Dhanvi Vedantham; A. Amalin Prince; Jac Fredo Agastinose Ronickom (Multim. Tools Appl., 2025)