Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
Background and objectives Artificial intelligence (AI) has branched out to various
applications in healthcare, such as health services management, predictive medicine …
applications in healthcare, such as health services management, predictive medicine …
[HTML][HTML] Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Abstract Machine learning methods offer great promise for fast and accurate detection and
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
Explainability of artificial intelligence methods, applications and challenges: A comprehensive survey
W Ding, M Abdel-Basset, H Hawash, AM Ali - Information Sciences, 2022 - Elsevier
The continuous advancement of Artificial Intelligence (AI) has been revolutionizing the
strategy of decision-making in different life domains. Regardless of this achievement, AI …
strategy of decision-making in different life domains. Regardless of this achievement, AI …
Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Multi-task deep learning for medical image computing and analysis: A review
The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …
conventional deep learning models are constructed for a single specific task, multi-task deep …
AI-Based human audio processing for COVID-19: A comprehensive overview
Abstract The Coronavirus (COVID-19) pandemic impelled several research efforts, from
collecting COVID-19 patients' data to screening them for virus detection. Some COVID-19 …
collecting COVID-19 patients' data to screening them for virus detection. Some COVID-19 …
Covid-MANet: Multi-task attention network for explainable diagnosis and severity assessment of COVID-19 from CXR images
A Sharma, PK Mishra - Pattern Recognition, 2022 - Elsevier
The devastating outbreak of Coronavirus Disease (COVID-19) cases in early 2020 led the
world to face health crises. Subsequently, the exponential reproduction rate of COVID-19 …
world to face health crises. Subsequently, the exponential reproduction rate of COVID-19 …
[HTML][HTML] CR19: A framework for preliminary detection of COVID-19 in cough audio signals using machine learning algorithms for automated medical diagnosis …
Today, there is a level of panic and chaos dominating the entire world due to the massive
outbreak in the second wave of COVID-19 disease. As the disease has numerous symptoms …
outbreak in the second wave of COVID-19 disease. As the disease has numerous symptoms …
[HTML][HTML] Explainable vision transformers and radiomics for covid-19 detection in chest x-rays
M Chetoui, MA Akhloufi - Journal of Clinical Medicine, 2022 - mdpi.com
The rapid spread of COVID-19 across the globe since its emergence has pushed many
countries' healthcare systems to the verge of collapse. To restrict the spread of the disease …
countries' healthcare systems to the verge of collapse. To restrict the spread of the disease …
Shallow decision trees for explainable k-means clustering
A number of recent works have employed decision trees for the construction of explainable
partitions that aim to minimize the k-means cost function. These works, however, largely …
partitions that aim to minimize the k-means cost function. These works, however, largely …