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

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Day 253 - West Midlands Police - Forensic Science Lab (7969822920).jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Signoroni NatComm23 14.png|240px]]</div>
'''"[[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]]"'''
'''"[[Journal:The need for informatics to support forensic pathology and death investigation|The need for informatics to support forensic pathology and death investigation]]"'''


As a result of their practice of medicine, [[Forensic science|forensic]] pathologists create a wealth of data regarding the causes of and reasons for sudden, unexpected or violent deaths. This data have been effectively used to protect the health and safety of the general public in a variety of ways despite current and historical limitations. These limitations include the lack of data standards between the thousands of death investigation (DI) systems in the United States, rudimentary electronic information systems for DI, and the lack of effective communications and interfaces between these systems. Collaboration between forensic pathology and [[health informatics|clinical informatics]] is required to address these shortcomings and a path forward has been proposed that will enable forensic pathology to maximize its effectiveness by providing timely and actionable [[information]] to public health and public safety agencies. ('''[[Journal:The need for informatics to support forensic pathology and death investigation|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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