[HTML][HTML] Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
Abstract Explainable Artificial Intelligence (XAI) is an emerging research topic of machine
learning aimed at unboxing how AI systems' black-box choices are made. This research field …
learning aimed at unboxing how AI systems' black-box choices are made. This research field …
Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches
COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
COVID‐19 diagnosis system by deep learning approaches
HK Bhuyan, C Chakraborty, Y Shelke… - Expert Systems, 2022 - Wiley Online Library
The novel coronavirus disease 2019 (COVID‐19) has been a severe health issue affecting
the respiratory system and spreads very fast from one human to other overall countries. For …
the respiratory system and spreads very fast from one human to other overall countries. For …
COVID-19 diagnosis: A review of rapid antigen, RT-PCR and artificial intelligence methods
As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused
5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to …
5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to …
Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography …
Background COVID-19 pandemic has currently no vaccines. Thus, the only feasible solution
for prevention relies on the detection of COVID-19-positive cases through quick and …
for prevention relies on the detection of COVID-19-positive cases through quick and …
COVID-19 detection from lung CT-scan images using transfer learning approach
A Halder, B Datta - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Since the onset of 2020, the spread of coronavirus disease (COVID-19) has rapidly
accelerated worldwide into a state of severe pandemic. COVID-19 has infected more than …
accelerated worldwide into a state of severe pandemic. COVID-19 has infected more than …
Systematic review of artificial intelligence in acute respiratory distress syndrome for COVID-19 lung patients: a biomedical imaging perspective
SARS-CoV-2 has infected over∼ 165 million people worldwide causing Acute Respiratory
Distress Syndrome (ARDS) and has killed∼ 3.4 million people. Artificial Intelligence (AI) has …
Distress Syndrome (ARDS) and has killed∼ 3.4 million people. Artificial Intelligence (AI) has …
Advance warning methodologies for covid-19 using chest x-ray images
Coronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its
first known detection in December 2019. As a result, accurate and reliable advance warning …
first known detection in December 2019. As a result, accurate and reliable advance warning …
Deep semi-supervised learning with contrastive learning and partial label propagation for image data
Y Gan, H Zhu, W Guo, G Xu, G Zou - Knowledge-Based Systems, 2022 - Elsevier
Deep semi-supervised learning is becoming an active research topic because it jointly
utilizes labeled and unlabeled samples in training deep neural networks. Recent advances …
utilizes labeled and unlabeled samples in training deep neural networks. Recent advances …
Explainable COVID-19 infections identification and delineation using calibrated pseudo labels
The upheaval brought by the arrival of the COVID-19 pandemic has continued to bring fresh
challenges over the past two years. During this COVID-19 pandemic, there has been a need …
challenges over the past two years. During this COVID-19 pandemic, there has been a need …