Role of artificial intelligence in radiogenomics for cancers in the era of precision medicine

S Saxena, B Jena, N Gupta, S Das, D Sarmah… - Cancers, 2022 - mdpi.com
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 …

COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A …

JS Suri, A Puvvula, M Biswas, M Majhail, L Saba… - Computers in biology …, 2020 - Elsevier
Artificial intelligence (AI) has penetrated the field of medicine, particularly the field of
radiology. Since its emergence, the highly virulent coronavirus disease 2019 (COVID-19) …

Hybrid deep learning segmentation models for atherosclerotic plaque in internal carotid artery B-mode ultrasound

PK Jain, N Sharma, AA Giannopoulos, L Saba… - Computers in biology …, 2021 - Elsevier
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™ …

Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A …

M Agarwal, S Agarwal, L Saba, GL Chabert… - Computers in biology …, 2022 - Elsevier
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 …

Economics of artificial intelligence in healthcare: diagnosis vs. treatment

NN Khanna, MA Maindarkar, V Viswanathan… - Healthcare, 2022 - mdpi.com
Motivation: The price of medical treatment continues to rise due to (i) an increasing
population;(ii) an aging human growth;(iii) disease prevalence;(iv) a rise in the frequency of …

Multi-modal bioelectrical signal fusion analysis based on different acquisition devices and scene settings: Overview, challenges, and novel orientation

J Li, Q Wang - Information Fusion, 2022 - Elsevier
Multi-modal fusion combines multiple modal information to overcome the limitation of
incomplete information expressed by a single modality, so as to realize the complementarity …

[HTML][HTML] Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: A narrative review for stroke application

L Saba, SS Sanagala, SK Gupta… - Annals of …, 2021 - ncbi.nlm.nih.gov
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 …

COVLIAS 2.0-cXAI: Cloud-based explainable deep learning system for COVID-19 lesion localization in computed tomography scans

JS Suri, S Agarwal, GL Chabert, A Carriero, A Paschè… - Diagnostics, 2022 - mdpi.com
Background: The previous COVID-19 lung diagnosis system lacks both scientific validation
and the role of explainable artificial intelligence (AI) for understanding lesion localization …

Far wall plaque segmentation and area measurement in common and internal carotid artery ultrasound using U-series architectures: An unseen Artificial Intelligence …

PK Jain, N Sharma, MK Kalra, A Johri, L Saba… - Computers in Biology …, 2022 - Elsevier
Stroke risk assessment using deep learning (DL) requires automated, accurate, and real-
time risk assessment while ensuring compact model size. Previous DL paradigms suffered …

Cardiovascular/stroke risk stratification in diabetic foot infection patients using deep learning-based artificial intelligence: an investigative study

NN Khanna, MA Maindarkar, V Viswanathan… - Journal of clinical …, 2022 - mdpi.com
A diabetic foot infection (DFI) is among the most serious, incurable, and costly to treat
conditions. The presence of a DFI renders machine learning (ML) systems extremely …