mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology

ABSTRACT Artur Yakimovich works in the field of computational virology and applies machine learning algorithms to study host-pathogen interactions. In this mSphere of Influence article, he reflects on two papers “Holographic Deep Learning for Rapid Optical Screening of Anthrax Spores” by Jo et al. (...

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Autor principal:	Artur Yakimovich
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2019
Materias:	anthrax artificial intelligence bioimage analysis computer vision convolutional neural networks deep learning Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/a3e7c16559e545e0a160af8d86ed51c0
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spelling	oai:doaj.org-article:a3e7c16559e545e0a160af8d86ed51c02021-11-15T15:22:21ZmSphere of Influence: the Rise of Artificial Intelligence in Infection Biology10.1128/mSphere.00315-192379-5042https://doaj.org/article/a3e7c16559e545e0a160af8d86ed51c02019-06-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSphere.00315-19https://doaj.org/toc/2379-5042ABSTRACT Artur Yakimovich works in the field of computational virology and applies machine learning algorithms to study host-pathogen interactions. In this mSphere of Influence article, he reflects on two papers “Holographic Deep Learning for Rapid Optical Screening of Anthrax Spores” by Jo et al. (Y. Jo, S. Park, J. Jung, J. Yoon, et al., Sci Adv 3:e1700606, 2017, https://doi.org/10.1126/sciadv.1700606) and “Bacterial Colony Counting with Convolutional Neural Networks in Digital Microbiology Imaging” by Ferrari and colleagues (A. Ferrari, S. Lombardi, and A. Signoroni, Pattern Recognition 61:629–640, 2017, https://doi.org/10.1016/j.patcog.2016.07.016). Here he discusses how these papers made an impact on him by showcasing that artificial intelligence algorithms can be equally applicable to both classical infection biology techniques and cutting-edge label-free imaging of pathogens.Artur YakimovichAmerican Society for Microbiologyarticleanthraxartificial intelligencebioimage analysiscomputer visionconvolutional neural networksdeep learningMicrobiologyQR1-502ENmSphere, Vol 4, Iss 3 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	anthrax artificial intelligence bioimage analysis computer vision convolutional neural networks deep learning Microbiology QR1-502
spellingShingle	anthrax artificial intelligence bioimage analysis computer vision convolutional neural networks deep learning Microbiology QR1-502 Artur Yakimovich mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology
description	ABSTRACT Artur Yakimovich works in the field of computational virology and applies machine learning algorithms to study host-pathogen interactions. In this mSphere of Influence article, he reflects on two papers “Holographic Deep Learning for Rapid Optical Screening of Anthrax Spores” by Jo et al. (Y. Jo, S. Park, J. Jung, J. Yoon, et al., Sci Adv 3:e1700606, 2017, https://doi.org/10.1126/sciadv.1700606) and “Bacterial Colony Counting with Convolutional Neural Networks in Digital Microbiology Imaging” by Ferrari and colleagues (A. Ferrari, S. Lombardi, and A. Signoroni, Pattern Recognition 61:629–640, 2017, https://doi.org/10.1016/j.patcog.2016.07.016). Here he discusses how these papers made an impact on him by showcasing that artificial intelligence algorithms can be equally applicable to both classical infection biology techniques and cutting-edge label-free imaging of pathogens.
format	article
author	Artur Yakimovich
author_facet	Artur Yakimovich
author_sort	Artur Yakimovich
title	mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology
title_short	mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology
title_full	mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology
title_fullStr	mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology
title_full_unstemmed	mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology
title_sort	msphere of influence: the rise of artificial intelligence in infection biology
publisher	American Society for Microbiology
publishDate	2019
url	https://doaj.org/article/a3e7c16559e545e0a160af8d86ed51c0
work_keys_str_mv	AT arturyakimovich msphereofinfluencetheriseofartificialintelligenceininfectionbiology
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mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology

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