The present and future of deep learning in radiology
Abstract The advent of Deep Learning (DL) is poised to dramatically change the delivery of
healthcare in the near future. Not only has DL profoundly affected the healthcare industry it …
healthcare in the near future. Not only has DL profoundly affected the healthcare industry it …
[HTML][HTML] Cerebral small vessel disease: a review focusing on pathophysiology, biomarkers, and machine learning strategies
E Cuadrado-Godia, P Dwivedi, S Sharma… - Journal of …, 2018 - ncbi.nlm.nih.gov
Cerebral small vessel disease (cSVD) has a crucial role in lacunar stroke and brain
hemorrhages and is a leading cause of cognitive decline and functional loss in elderly …
hemorrhages and is a leading cause of cognitive decline and functional loss in elderly …
Hybrid deep learning segmentation models for atherosclerotic plaque in internal carotid artery B-mode ultrasound
The automated and accurate carotid plaque segmentation in B-mode ultrasound (US) is an
essential part of stroke risk stratification. Previous segmented methods used AtheroEdge™ …
essential part of stroke risk stratification. Previous segmented methods used AtheroEdge™ …
Role of ensemble deep learning for brain tumor classification in multiple magnetic resonance imaging sequence data
The biopsy is a gold standard method for tumor grading. However, due to its invasive nature,
it has sometimes proved fatal for brain tumor patients. As a result, a non-invasive computer …
it has sometimes proved fatal for brain tumor patients. As a result, a non-invasive computer …
Symtosis: A liver ultrasound tissue characterization and risk stratification in optimized deep learning paradigm
Abstract Background and Objective Fatty Liver Disease (FLD)-a disease caused by
deposition of fat in liver cells, is predecessor to terminal diseases such as liver cancer. The …
deposition of fat in liver cells, is predecessor to terminal diseases such as liver cancer. The …
A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence
Abstract COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million
fatalities as of December 21, 2020. The primary cause of death due to COVID-19 is Acute …
fatalities as of December 21, 2020. The primary cause of death due to COVID-19 is Acute …
A novel block imaging technique using nine artificial intelligence models for COVID-19 disease classification, characterization and severity measurement in lung …
Computer Tomography (CT) is currently being adapted for visualization of COVID-19 lung
damage. Manual classification and characterization of COVID-19 may be biased depending …
damage. Manual classification and characterization of COVID-19 may be biased depending …
A powerful paradigm for cardiovascular risk stratification using multiclass, multi-label, and ensemble-based machine learning paradigms: A narrative review
Abstract Background and Motivation: Cardiovascular disease (CVD) causes the highest
mortality globally. With escalating healthcare costs, early non-invasive CVD risk assessment …
mortality globally. With escalating healthcare costs, early non-invasive CVD risk assessment …
[HTML][HTML] Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: A narrative review for stroke application
Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the
United States of America and globally. Carotid arterial plaque, a cause and also a marker of …
United States of America and globally. Carotid arterial plaque, a cause and also a marker of …
Attention-based UNet deep learning model for plaque segmentation in carotid ultrasound for stroke risk stratification: an artificial intelligence paradigm
Stroke and cardiovascular diseases (CVD) significantly affect the world population. The
early detection of such events may prevent the burden of death and costly surgery …
early detection of such events may prevent the burden of death and costly surgery …