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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Murch FrontBioengBiotech2019 6.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Signoroni NatComm23 14.png|240px]]</div>
'''"[[Journal:Cyberbiosecurity: An emerging new discipline to help safeguard the bioeconomy|Cyberbiosecurity: An emerging new discipline to help safeguard the bioeconomy]]"'''
'''"[[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]]"'''


Cyberbiosecurity is being proposed as a formal new enterprise which encompasses cybersecurity, cyber-physical security, and biosecurity as applied to biological and biomedical-based systems. In recent years, an array of important meetings and public discussions, commentaries, and publications have occurred that highlight numerous vulnerabilities. While necessary first steps, they do not provide a systematized structure for effectively promoting communication, education and training, elucidation, and prioritization for analysis, research, development, testing and evaluation, and implementation of scientific and technological standards of practice, policy, or regulatory or legal considerations for protecting the bioeconomy. Further, experts in biosecurity and cybersecurity are generally not aware of each other's domains, expertise, perspectives, priorities, or where mutually supported opportunities exist for which positive outcomes could result. ('''[[Journal:Cyberbiosecurity: An emerging new discipline to help safeguard the bioeconomy|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...)
Recently featured: