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[HTML][HTML] Role of artificial intelligence in radiogenomics for cancers in the era of precision medicine
Simple Summary Recently, radiogenomics has played a significant role and offered a new
understanding of cancer's biology and behavior in response to standard therapy. It also …
understanding of cancer's biology and behavior in response to standard therapy. It also …
Blockchain, artificial intelligence, and healthcare: the tripod of future—a narrative review
The fusion of blockchain and artificial intelligence (AI) marks a paradigm shift in healthcare,
addressing critical challenges in securing electronic health records (EHRs), ensuring data …
addressing critical challenges in securing electronic health records (EHRs), ensuring data …
Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A …
Abstract Background COVLIAS 1.0: an automated lung segmentation was designed for
COVID-19 diagnosis. It has issues related to storage space and speed. This study shows …
COVID-19 diagnosis. It has issues related to storage space and speed. This study shows …
[HTML][HTML] Ensemble deep learning derived from transfer learning for classification of COVID-19 patients on hybrid deep-learning-based lung segmentation: a data …
AK Dubey, GL Chabert, A Carriero, A Pasche… - Diagnostics, 2023 - mdpi.com
Background and motivation: Lung computed tomography (CT) techniques are high-
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …
A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework
Background Early and automated detection of carotid plaques prevents strokes, which are
the second leading cause of death worldwide according to the World Health Organization …
the second leading cause of death worldwide according to the World Health Organization …
Ten fast transfer learning models for carotid ultrasound plaque tissue characterization in augmentation framework embedded with heatmaps for stroke risk stratification
Background and Purpose: Only 1–2% of the internal carotid artery asymptomatic plaques
are unstable as a result of> 80% stenosis. Thus, unnecessary efforts can be saved if these …
are unstable as a result of> 80% stenosis. Thus, unnecessary efforts can be saved if these …
[HTML][HTML] Cardiovascular/stroke risk stratification in Parkinson's disease patients using atherosclerosis pathway and artificial intelligence paradigm: a systematic review
Parkinson's disease (PD) is a severe, incurable, and costly condition leading to heart failure.
The link between PD and cardiovascular disease (CVD) is not available, leading to …
The link between PD and cardiovascular disease (CVD) is not available, leading to …
[HTML][HTML] Recent advances in machine learning applied to ultrasound imaging
M Micucci, A Iula - Electronics, 2022 - mdpi.com
Machine learning (ML) methods are pervading an increasing number of fields of application
because of their capacity to effectively solve a wide variety of challenging problems. The …
because of their capacity to effectively solve a wide variety of challenging problems. The …
[HTML][HTML] Ultrasound-based image analysis for predicting carotid artery stenosis risk: A comprehensive review of the problem, techniques, datasets, and future …
The carotid artery is a major blood vessel that supplies blood to the brain. Plaque buildup in
the arteries can lead to cardiovascular diseases such as atherosclerosis, stroke, ruptured …
the arteries can lead to cardiovascular diseases such as atherosclerosis, stroke, ruptured …
[HTML][HTML] COVLIAS 1.0: lung segmentation in COVID-19 computed tomography scans using hybrid deep learning artificial intelligence models
Background: COVID-19 lung segmentation using Computed Tomography (CT) scans is
important for the diagnosis of lung severity. The process of automated lung segmentation is …
important for the diagnosis of lung severity. The process of automated lung segmentation is …