collaborators

7 papers

cs.LG2025

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…

cs.LG2025

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…

physics.optics2025

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…

eess.AS2025

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…

eess.AS2025

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…

eess.SP2025

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…