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 …

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 …

[HTML][HTML] Deep learning framework for rapid and accurate respiratory COVID-19 prediction using chest X-ray images

CC Ukwuoma, D Cai, MBB Heyat, O Bamisile… - Journal of King Saud …, 2023 - Elsevier
COVID-19 is a contagious disease that affects the human respiratory system. Infected
individuals may develop serious illnesses, and complications may result in death. Using …

Segmentation-based classification deep learning model embedded with explainable AI for COVID-19 detection in chest X-ray scans

N Sharma, L Saba, NN Khanna, MK Kalra, MM Fouda… - Diagnostics, 2022 - mdpi.com
Background and Motivation: COVID-19 has resulted in a massive loss of life during the last
two years. The current imaging-based diagnostic methods for COVID-19 detection in …

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 …

Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: a neuro-oncological investigation

S Saxena, B Jena, B Mohapatra, N Gupta… - Computers in Biology …, 2023 - Elsevier
Abstract Background The O6-methylguanine-DNA methyltransferase (MGMT) is a
deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential …

Blockchain, artificial intelligence, and healthcare: the tripod of future—a narrative review

A Bathula, SK Gupta, S Merugu, L Saba… - Artificial Intelligence …, 2024 - Springer
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 …

Five strategies for bias estimation in artificial intelligence-based hybrid deep learning for acute respiratory distress syndrome COVID-19 lung infected patients using …

JS Suri, S Agarwal, B Jena, S Saxena… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Coronavirus 2019 (COVID-19) has led to a global pandemic infecting 224 million people
and has caused 4.6 million deaths. Nearly 80 Artificial Intelligence (AI) articles have been …

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 …

COVLIAS 1.0: lung segmentation in COVID-19 computed tomography scans using hybrid deep learning artificial intelligence models

JS Suri, S Agarwal, R Pathak, V Ketireddy, M Columbu… - Diagnostics, 2021 - mdpi.com
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 …