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Deep learning for computer-assisted diagnosis of hereditary diffuse gastric cancer.
In Journal of pathology and translational medicine
Background :
Materials and Methods :
Results :
Conclusion :
Rasmussen Sean A, Arnason Thomas, Huang Weei-Yuarn
2021-Jan-22
Computer-assisted diagnosis, Deep learning, Machine learning, Pathology, Stomach neoplasms

Use of Artificial Intelligence to understand adults' thoughts and behaviours relating to COVID-19.
In Perspectives in public health
AIMS :
METHODS :
RESULTS :
CONCLUSIONS :
Flint S W, Piotrkowicz A, Watts K
2021-Jan-21
Artificial Intelligence, COVID-19, attitudes, behaviours, lockdown

Genomic Mutations and Changes in Protein Secondary Structure and Solvent Accessibility of SARS-CoV-2 (COVID-19 Virus)
bioRxiv Preprint
Nguyen, T. T.; Pathirana, P. N.; Nguyen, T.; Nguyen, Q. V. H.; Bhatti, A.; Nguyen, D. C.; Nguyen, D. T.; Nguyen, N. D.; Creighton, D.; Abdelrazek, M.
2021-01-22

A multi-perspective combined recall and rank framework for Chinese procedure terminology normalization
ArXiv Preprint
Ming Liang, Kui Xue, Tong Ruan
2021-01-22
Machine learning combining CT findings and clinical parameters improves prediction of length of stay and ICU admission in torso trauma.
In European radiology ; h5-index 62.0
OBJECTIVE :
MATERIALS AND METHODS :
RESULTS :
CONCLUSIONS :
KEY POINTS :
Staziaki Pedro VinÃcius, Wu Di, Rayan Jesse C, Santo Irene Dixe de Oliveira, Nan Feng, Maybury Aaron, Gangasani Neha, Benador Ilan, Saligrama Venkatesh, Scalera Jonathan, Anderson Stephan W
2021-Jan-21
Accidental injuries, diagnostic imaging, Artificial intelligence, Length of stay, Machine learning, Multidetector computed tomography

Regulatory genes identification within functional genomics experiments for tissue classification into binary classes via machine learning techniques.
In JPMA. The Journal of the Pakistan Medical Association
OBJECTIVE :
Method :
RESULTS :
CONCLUSIONS :
Wazir Bushra, Khan Dost Muhammad, Khalil Umair, Hamraz Muhammad, Gul Naz, Khan Zardad
2020-Dec
** Gene selection, classification, random forest, cancer, microarray gene expression \n\n**
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