9 citations · 12 across the 13 of their papers we have counts for
13 papers
XVAE-WMT: Explainable Wavelet-Temporal Variational Autoencoder for Blind Source Separation of Heart and Lung Sounds
Yasaman Torabi, Shahram Shirani, James P. Reilly
The separation of cardiovascular sounds is a critical task in biomedical signal processing. In this paper, we introduce XVAE-WMT1, an unsupervised explainable generative AI algorit…
Physics-Informed Graph Neural Network for Inverse Design of Integrated Photonic Biosensors
Yasaman Torabi, Amirali Ekhteraei, Mohammad Khajezadeh
Integrated photonic biosensors provide compact, highly sensitive, and label-free platforms for biochemical detection, making them attractive for on-chip and real-time sensing appli…
AI-Driven Cardiorespiratory Signal Processing: Separation, Clustering, and Anomaly Detection
Yasaman Torabi
This research applies artificial intelligence (AI) to separate, cluster, and analyze cardiorespiratory sounds. We recorded a new dataset (HLS-CMDS) and developed several AI models,…
NeuroMambaLLM: Dynamic Graph Learning of fMRI Functional Connectivity in Autistic Brains Using Mamba and Language Model Reasoning
Yasaman Torabi, Parsa Razmara, Hamed Ajorlou +1
Large Language Models (LLMs) have demonstrated strong semantic reasoning across multimodal domains. However, their integration with graph-based models of brain connectivity remains…
QuPCG: Quantum Convolutional Neural Network for Detecting Abnormal Patterns in PCG Signals
Yasaman Torabi, Shahram Shirani, James P. Reilly
Early identification of abnormal physiological patterns is essential for the timely detection of cardiac disease. This work introduces a hybrid quantum-classical convolutional neur…
Chem-NMF: Multi-layer -divergence Non-Negative Matrix Factorization for Cardiorespiratory Disease Clustering, with Improved Convergence Inspired by Chemical Catalysts and Rigorous Asymptotic Analysis
Yasaman Torabi, Shahram Shirani, James P. Reilly
Non-Negative Matrix Factorization (NMF) is an unsupervised learning method offering low-rank representations across various domains such as audio processing, biomedical signal anal…
Quantum Biosensors on Chip: A Review from Electronic and Photonic Integrated Circuits to Future Integrated Quantum Photonic Circuits
Yasaman Torabi, Shahram Shirani, James P. Reilly
Quantum biosensors offer a promising route to overcome the sensitivity and specificity limitations of conventional biosensing technologies. Their ability to detect biochemical sign…
Large Language Models and Non-Negative Matrix Factorization for Bioacoustic Signal Decomposition
Yasaman Torabi, Shahram Shirani, James P. Reilly
Large language models have shown a remarkable ability to extract meaning from unstructured data, offering new ways to interpret biomedical signals beyond traditional numerical meth…
Blind Source Separation in Biomedical Signals Using Variational Methods
Yasaman Torabi, Shahram Shirani, James P. Reilly
This study introduces a novel unsupervised approach for separating overlapping heart and lung sounds using variational autoencoders (VAEs). In clinical settings, these sounds often…
Large Language Model-based Nonnegative Matrix Factorization For Cardiorespiratory Sound Separation
Yasaman Torabi, Shahram Shirani, James P. Reilly
This study represents the first integration of large language models (LLMs) with non-negative matrix factorization (NMF), marking a novel advancement in the source separation field…
Design and Implementation of an IoT-based Respiratory Motion Sensor
Bardia Baraeinejad, Maryam Forouzesh, Saba Babaei +3
In the last few decades, several wearable devices have been designed to monitor respiration rate in an effort to capture pulmonary signals with higher accuracy and reduce patients'…
MEMS and ECM Sensor Technologies for Cardiorespiratory Sound Monitoring - A Comprehensive Review
Yasaman Torabi, Shahram Shirani, James P. Reilly +1
This paper presents a comprehensive review of cardiorespiratory auscultation sensing devices (i.e., stethoscopes), which is useful for understanding the theoretical aspects and pra…
A New Non-Negative Matrix Factorization Approach for Blind Source Separation of Cardiovascular and Respiratory Sound Based on the Periodicity of Heart and Lung Function
Yasaman Torabi, Shahram Shirani, James P. Reilly
Auscultation provides a rich diversity of information to diagnose cardiovascular and respiratory diseases. However, sound auscultation is challenging due to noise. In this study, a…