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[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
G Yang, Q Ye, J ** review on the use of natural language processing in research on political polarization: trends and research prospects
R Németh - Journal of computational social science, 2023 - Springer
As part of the “text-as-data” movement, Natural Language Processing (NLP) provides a
computational way to examine political polarization. We conducted a methodological …
computational way to examine political polarization. We conducted a methodological …
A medical multimodal large language model for future pandemics
Deep neural networks have been integrated into the whole clinical decision procedure
which can improve the efficiency of diagnosis and alleviate the heavy workload of …
which can improve the efficiency of diagnosis and alleviate the heavy workload of …
[КНИГА][B] Resisting AI: An anti-fascist approach to artificial intelligence
D McQuillan - 2022 - books.google.com
Artificial Intelligence (AI) is everywhere, yet it causes damage to society in ways that can't be
fixed. Instead of hel** to address our current crises, AI causes divisions that limit people's …
fixed. Instead of hel** to address our current crises, AI causes divisions that limit people's …
[HTML][HTML] The use of artificial intelligence systems in diagnosis of pneumonia via signs and symptoms: A systematic review
Artificial Intelligence (AI) systems using symptoms/signs to detect respiratory diseases may
improve diagnosis especially in limited resource settings. Heterogeneity in such AI systems …
improve diagnosis especially in limited resource settings. Heterogeneity in such AI systems …
[HTML][HTML] Robust weakly supervised learning for COVID-19 recognition using multi-center CT images
The world is currently experiencing an ongoing pandemic of an infectious disease named
coronavirus disease 2019 (ie, COVID-19), which is caused by the severe acute respiratory …
coronavirus disease 2019 (ie, COVID-19), which is caused by the severe acute respiratory …
Using alignment-free and pattern mining methods for SARS-CoV-2 genome analysis
Examining the genome sequences of the SARS-CoV-2 virus, that causes the respiratory
disease known as coronavirus disease 2019 (COVID-19), play important role in the proper …
disease known as coronavirus disease 2019 (COVID-19), play important role in the proper …
Reinforcement learning based diagnosis and prediction for COVID-19 by optimizing a mixed cost function from CT images
S Chen, M Liu, P Deng, J Deng, Y Yuan… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
A novel coronavirus disease (COVID-19) is a pandemic disease has caused 4 million
deaths and more than 200 million infections worldwide (as of August 4, 2021). Rapid and …
deaths and more than 200 million infections worldwide (as of August 4, 2021). Rapid and …
A novel machine learning‐based analytical framework for automatic detection of COVID‐19 using chest X‐ray images
Considering the prevailing scenario of COVID‐19 pandemic, early detection of the disease
is an important and crucial step in disease management. Early detection and correct …
is an important and crucial step in disease management. Early detection and correct …
[HTML][HTML] Machine learning to predict in-hospital mortality in COVID-19 patients using computed tomography-derived pulmonary and vascular features
S Schiaffino, M Codari, A Cozzi, D Albano… - Journal of personalized …, 2021 - mdpi.com
Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients
and can be assessed with unenhanced chest computed tomography (CT), widely used as a …
and can be assessed with unenhanced chest computed tomography (CT), widely used as a …