Human activity recognition in artificial intelligence framework: a narrative review

N Gupta, SK Gupta, RK Pathak, V Jain… - Artificial intelligence …, 2022 - Springer
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …

An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review

S Das, GK Nayak, L Saba, M Kalra, JS Suri… - Computers in biology and …, 2022 - Elsevier
Background Artificial intelligence (AI) has become a prominent technique for medical
diagnosis and represents an essential role in detecting brain tumors. Although AI-based …

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 …

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 …

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 …

Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review

JS Suri, M Bhagawati, S Paul, A Protogeron… - Computers in biology …, 2022 - Elsevier
Abstract Background Artificial Intelligence (AI), in particular, machine learning (ML) has
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …

Integrative approaches in acute ischemic stroke: from symptom recognition to future innovations

VM Saceleanu, C Toader, H Ples… - Biomedicines, 2023 - mdpi.com
Among the high prevalence of cerebrovascular diseases nowadays, acute ischemic stroke
stands out, representing a significant worldwide health issue with important socio-economic …

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] 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 …

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 …