Difference between revisions of "Template:Article of the week"

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'''"[[Journal:Emerging cybersecurity threats in radiation oncology|Emerging cybersecurity threats in radiation oncology]]"'''
'''"[[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology]]"'''


Modern image-guided radiation therapy is dependent on information technology and data storage applications that, like any other digital technology, are at risk from cyberattacks. Owing to a recent escalation in cyberattacks affecting radiation therapy treatments, the American Society for Radiation Oncology's ''Advances in Radiation Oncology'' is inaugurating a new special manuscript category devoted to [[cybersecurity]] issues. We conducted a review of emerging cybersecurity threats and a literature review of cyberattacks that affected [[Radiation oncologist|radiation oncology]] practices. In the last 10 years, numerous attacks have led to an interruption of radiation therapy for thousands of patients, and some of these catastrophic incidents have been described as being worse than [[coronavirus disease 2019]]'s impact on healthcare centers in New Zealand ... ('''[[Journal:Emerging cybersecurity threats in radiation oncology|Full article...]]''')<br />
Full [[laboratory automation]] is revolutionizing work habits in an increasing number of clinical [[microbiology]] facilities worldwide, generating huge streams of [[Imaging|digital images]] for interpretation. Contextually, [[deep learning]] (DL) architectures are leading to paradigm shifts in the way computers can assist with difficult visual interpretation tasks in several domains. At the crossroads of these epochal trends, we present a system able to tackle a core task in clinical microbiology, namely the global interpretation of diagnostic [[Bacteria|bacterial]] [[Cell culture|culture]] plates, including presumptive [[pathogen]] identification. This is achieved by decomposing the problem into a hierarchy of complex subtasks and addressing them with a multi-network architecture we call DeepColony ... ('''[[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Full article...]]''')<br />
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Latest revision as of 15:02, 3 June 2024

Fig1 Signoroni NatComm23 14.png

"Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology"

Full laboratory automation is revolutionizing work habits in an increasing number of clinical microbiology facilities worldwide, generating huge streams of digital images for interpretation. Contextually, deep learning (DL) architectures are leading to paradigm shifts in the way computers can assist with difficult visual interpretation tasks in several domains. At the crossroads of these epochal trends, we present a system able to tackle a core task in clinical microbiology, namely the global interpretation of diagnostic bacterial culture plates, including presumptive pathogen identification. This is achieved by decomposing the problem into a hierarchy of complex subtasks and addressing them with a multi-network architecture we call DeepColony ... (Full article...)
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