Search Results for author: Ali Bahrami Rad

Found 11 papers, 2 papers with code

Explainable Artificial Intelligence for Quantifying Interfering and High-Risk Behaviors in Autism Spectrum Disorder in a Real-World Classroom Environment Using Privacy-Preserving Video Analysis

no code implementations31 Jul 2024 Barun Das, Conor Anderson, Tania Villavicencio, Johanna Lantz, Jenny Foster, Theresa Hamlin, Ali Bahrami Rad, Gari D. Clifford, Hyeokhyen Kwon

To the best of our knowledge, this is the first work that shows the promise of objectively quantifying behaviors in ASD in a real-world environment, which is an important step toward the development of a practical tool that can ease the burden of data collection for classroom staff.

Explainable artificial intelligence Group Activity Recognition +1

A Data-Driven Gaussian Process Filter for Electrocardiogram Denoising

no code implementations6 Jan 2023 Mircea Dumitru, Qiao Li, Erick Andres Perez Alday, Ali Bahrami Rad, Gari D. Clifford, Reza Sameni

Objective: Gaussian Processes (GP)-based filters, which have been effectively used for various applications including electrocardiogram (ECG) filtering can be computationally demanding and the choice of their hyperparameters is typically ad hoc.

Denoising Gaussian Processes

Mythological Medical Machine Learning: Boosting the Performance of a Deep Learning Medical Data Classifier Using Realistic Physiological Models

no code implementations28 Dec 2021 Ismail Sadiq, Erick A. Perez-Alday, Amit J. Shah, Ali Bahrami Rad, Reza Sameni, Gari D. Clifford

Objective: To determine if a realistic, but computationally efficient model of the electrocardiogram can be used to pre-train a deep neural network (DNN) with a wide range of morphologies and abnormalities specific to a given condition - T-wave Alternans (TWA) as a result of Post-Traumatic Stress Disorder, or PTSD - and significantly boost performance on a small database of rare individuals.

Transfer Learning

Kalman-based Spectro-Temporal ECG Analysis using Deep Convolutional Networks for Atrial Fibrillation Detection

no code implementations12 Dec 2018 Zheng Zhao, Simo Särkkä, Ali Bahrami Rad

In this article, we propose a novel ECG classification framework for atrial fibrillation (AF) detection using spectro-temporal representation (i. e., time varying spectrum) and deep convolutional networks.

Atrial Fibrillation Detection ECG Classification +1

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