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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Andellini BMCMedInfoDecMak2017 17-1.gif|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Signoroni NatComm23 14.png|240px]]</div>
'''"[[Journal:Experimental application of business process management technology to manage clinical pathways: A pediatric kidney transplantation follow-up case|Experimental application of business process management technology to manage clinical pathways: A pediatric kidney transplantation follow-up case]]"'''
'''"[[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]]"'''


Using a business process management platform, we implemented a specific application to manage the clinical pathway of pediatric patients, and we monitored the activities of the coordinator in charge of case management during a six-month period (from June 2015 to November 2015) using two methodologies: the traditional procedure and the one under study. The application helped physicians and nurses to optimize the amount of time and resources devoted to management purposes. In particular, time reduction was close to 60%. In addition, the reduction of data duplication, the integration of event management, and the efficient collection of data improved the quality of the service. The use of business process management technology, usually related to well-defined processes with high management costs, is an established procedure in multiple environments; its use in healthcare, however, is innovative. ('''[[Journal:Experimental application of business process management technology to manage clinical pathways: A pediatric kidney transplantation follow-up case|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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