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Human activity recognition in artificial intelligence framework: a narrative review
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 …
acquisition devices such as smartphones, video cameras, and its ability to capture human …
Leveraging machine learning and artificial intelligence to improve peripheral artery disease detection, treatment, and outcomes
Peripheral artery disease is an atherosclerotic disorder which, when present, portends poor
patient outcomes. Low diagnosis rates perpetuate poor management, leading to limb loss …
patient outcomes. Low diagnosis rates perpetuate poor management, leading to limb loss …
[HTML][HTML] Economics of artificial intelligence in healthcare: diagnosis vs. treatment
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 …
population;(ii) an aging human growth;(iii) disease prevalence;(iv) a rise in the frequency of …
[HTML][HTML] A deep convolutional neural network for the early detection of heart disease
Heart disease is one of the key contributors to human death. Each year, several people die
due to this disease. According to the WHO, 17.9 million people die each year due to heart …
due to this disease. According to the WHO, 17.9 million people die each year due to heart …
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™ …
[HTML][HTML] Segmentation-based classification deep learning model embedded with explainable AI for COVID-19 detection in chest X-ray scans
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 …
two years. The current imaging-based diagnostic methods for COVID-19 detection in …
[HTML][HTML] Brain tumor characterization using radiogenomics in artificial intelligence framework
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 …
the biology and behaviour of cancer in response to conventional treatments. One of the most …
Blockchain, artificial intelligence, and healthcare: the tripod of future—a narrative review
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 …
addressing critical challenges in securing electronic health records (EHRs), ensuring data …
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 …
[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 …
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …