Narendra N. Khanna
Orcid: 0000-0002-6935-0039
According to our database1,
Narendra N. Khanna
authored at least 19 papers
between 2018 and 2024.
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Bibliography
2024
Blockchain, artificial intelligence, and healthcare: the tripod of future - a narrative review.
Artif. Intell. Rev., September, 2024
Multim. Tools Appl., February, 2024
2023
Prediction of O-6-methylguanine-DNA methyltransferase and overall survival of the patients suffering from glioblastoma using MRI-based hybrid radiomics signatures in machine and deep learning framework.
Neural Comput. Appl., June, 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
Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review.
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
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
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
2019
Effect of carotid image-based phenotypes on cardiovascular risk calculator: AECRS1.0.
Medical Biol. Eng. Comput., 2019
Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study.
Comput. Biol. Medicine, 2019
Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach.
Comput. Biol. Medicine, 2019
2018
Morphologic TPA (mTPA) and composite risk score for moderate carotid atherosclerotic plaque is strongly associated with HbA1c in diabetes cohort.
Comput. Biol. Medicine, 2018
Deep learning strategy for accurate carotid intima-media thickness measurement: An ultrasound study on Japanese diabetic cohort.
Comput. Biol. Medicine, 2018
Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: A review.
Comput. Biol. Medicine, 2018