Area of research
Cardiology and Cardiovascular Medicine · Cognitive Neuroscience
Research interest
Research interests include Heart Rate Variability and Autonomic Control, EEG and Brain-Computer Interfaces, Non-Invasive Vital Sign Monitoring, and ECG Monitoring and Analysis.
Fusing Tabular Features and Deep Learning for Fetal Heart Rate Analysis: A Clinically Interpretable Model for Fetal Compromise Detection
Detecting Smart Ponzi Schemes on Blockchain Using Machine Learning: A Comprehensive Survey
CONSENSUS: Consensus-based Systematic Evidence Synthesis for Forensic Risk Profiling of Cryptocurrency Mixers
Minimum Foot Clearance Prediction in Stroke Survivors: A Transformer-Based Approach
NeuroSleepNet: An Explainable Multi-Head Attention-Based Framework With Spatial and Multi-Scale Independent Temporal Context Learning for Automatic Sleep Stage Scoring
Cross-Database Evaluation of Deep Learning Methods for Intrapartum Cardiotocography Classification
Application-Aware Real-Time Network Resource Allocation for Industry 5.0
Adversarial Masked Autoencoders Are Robust Vision Learners
Identifying Suspicious Blockchain Transactions using Clustering with Explainability
Zero-shot Stroke Lesion Segmentation via CAM-guided Prompting of MedSAM2
RepMedGAN: Self-supervised Representation-guided Medical GAN for Label-free Medical Image Synthesis
Rethinking Masked Image Modeling for Ultrasound Image Denoising
A Survey of Wearable Sensors and Machine Learning Algorithms for Automated Stroke Rehabilitation
Unified Feature Engineering for Detection of Malicious Entities in Blockchain Networks
Network Resource Allocation for Industry 4.0 With Delay and Safety Constraints
EDAF: Early Detection of Atrial Fibrillation from Post-stroke Brain MRI
A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments
Computerised Cardiotocography Analysis for the Automated Detection of Fetal Compromise during Labour: A Review
Performance of a Convolutional Neural Network Derived From PPG Signal in Classifying Sleep Stages
Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions
Detection of fetal arrhythmias in non-invasive fetal ECG recordings using data-driven entropy profiling
A Real-Time Tunable ECG Noise-Aware System for IoT-Enabled Devices
Achieving AI-Enabled Robust End-to-End Quality of Experience Over Backhaul Radio Access Networks
Guest Editorial: Computational Intelligence for Human-in-the-Loop Cyber Physical Systems
An Application Placement Technique for Concurrent IoT Applications in Edge and Fog Computing Environments
Missing Data Imputation With Bayesian Maximum Entropy for Internet of Things Applications
Identifying Groups of Fake Reviewers Using a Semisupervised Approach
Personalized Anatomic Modeling for Noninvasive Fetal ECG: Methodology and Applications
Upper limb movement profiles during spontaneous motion in acute stroke
Novel Measures of Similarity and Asymmetry in Upper Limb Activities for Identifying Hemiparetic Severity in Stroke Survivors