Amer M. Johri
Orcid: 0000-0001-7044-8212
According to our database1,
Amer M. Johri
authored at least 19 papers
between 2020 and 2024.
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Bibliography
2024
Multim. Tools Appl., February, 2024
MultiNet 2.0: A lightweight attention-based deep learning network for stenosis measurement in carotid ultrasound scans and cardiovascular risk assessment.
Comput. Medical Imaging Graph., 2024
2023
UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias.
IEEE Access, 2023
2022
Ensemble Machine Learning and Its Validation for Prediction of Coronary Artery Disease and Acute Coronary Syndrome Using Focused Carotid Ultrasound.
IEEE Trans. Instrum. Meas., 2022
Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review.
Comput. Biol. Medicine, 2022
A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework.
Comput. Biol. Medicine, 2022
Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization.
Comput. Biol. Medicine, 2022
A machine learning framework for risk prediction of multi-label cardiovascular events based on focused carotid plaque B-Mode ultrasound: A Canadian study.
Comput. Biol. Medicine, 2022
Far wall plaque segmentation and area measurement in common and internal carotid artery ultrasound using U-series architectures: An unseen Artificial Intelligence paradigm for stroke risk assessment.
Comput. Biol. Medicine, 2022
Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0.
Comput. Biol. Medicine, 2022
2021
A Multicenter Study on Carotid Ultrasound Plaque Tissue Characterization and Classification Using Six Deep Artificial Intelligence Models: A Stroke Application.
IEEE Trans. Instrum. Meas., 2021
Wilson disease tissue classification and characterization using seven artificial intelligence models embedded with 3D optimization paradigm on a weak training brain magnetic resonance imaging datasets: a supercomputer application.
Medical Biol. Eng. Comput., 2021
A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework.
J. Digit. Imaging, 2021
A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence.
Comput. Biol. Medicine, 2021
Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography lungs.
Int. J. Comput. Assist. Radiol. Surg., 2021
2020
Low-Cost Office-Based Cardiovascular Risk Stratification Using Machine Learning and Focused Carotid Ultrasound in an Asian-Indian Cohort.
J. Medical Syst., 2020
COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review.
Comput. Biol. Medicine, 2020
3-D optimized classification and characterization artificial intelligence paradigm for cardiovascular/stroke risk stratification using carotid ultrasound-based delineated plaque: Atheromatic™ 2.0.
Comput. Biol. Medicine, 2020
Artificial intelligence framework for predictive cardiovascular and stroke risk assessment models: A narrative review of integrated approaches using carotid ultrasound.
Comput. Biol. Medicine, 2020