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 …

Brain tumor characterization using radiogenomics in artificial intelligence framework

B Jena, S Saxena, GK Nayak, A Balestrieri, N Gupta… - Cancers, 2022 - mdpi.com
Simple Summary Radiogenomics is a relatively new advancement in the understanding of
the biology and behaviour of cancer in response to conventional treatments. One of the most …

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 …

[HTML][HTML] AI-assisted Screening and Prevention Programs for Diseases

M Farrokhi, A Moeini, F Taheri, M Farrokhi… - Kindle, 2023 - preferpub.org
AI-assisted screening and prevention programs have the potential to revolutionize disease
management and improve public health outcomes. By harnessing the power of artificial …

Bias investigation in artificial intelligence systems for early detection of Parkinson's disease: a narrative review

S Paul, M Maindarkar, S Saxena, L Saba, M Turk… - Diagnostics, 2022 - mdpi.com
Background and Motivation: Diagnosis of Parkinson's disease (PD) is often based on
medical attention and clinical signs. It is subjective and does not have a good prognosis …

A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework

SS Skandha, A Nicolaides, SK Gupta… - Computers in biology …, 2022 - Elsevier
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 …

Attention-based UNet deep learning model for plaque segmentation in carotid ultrasound for stroke risk stratification: an artificial intelligence paradigm

PK Jain, A Dubey, L Saba, NN Khanna… - Journal of …, 2022 - mdpi.com
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 …

Unseen artificial intelligence—Deep learning paradigm for segmentation of low atherosclerotic plaque in carotid ultrasound: A multicenter cardiovascular study

PK Jain, N Sharma, L Saba, KI Paraskevas, MK Kalra… - Diagnostics, 2021 - mdpi.com
Background: The early detection of carotid wall plaque is recommended in the prevention of
cardiovascular disease (CVD) in moderate-risk patients. Previous techniques for B-mode …