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 …
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™ …
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 …
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 …
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 …
population;(ii) an aging human growth;(iii) disease prevalence;(iv) a rise in the frequency of …
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 …
A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence
Abstract COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million
fatalities as of December 21, 2020. The primary cause of death due to COVID-19 is Acute …
fatalities as of December 21, 2020. The primary cause of death due to COVID-19 is Acute …
A novel block imaging technique using nine artificial intelligence models for COVID-19 disease classification, characterization and severity measurement in lung …
Computer Tomography (CT) is currently being adapted for visualization of COVID-19 lung
damage. Manual classification and characterization of COVID-19 may be biased depending …
damage. Manual classification and characterization of COVID-19 may be biased depending …
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 …
the second leading cause of death worldwide according to the World Health Organization …