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:Fig1 Ifriza Matrix23 13-1.png|240px]]</div>
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'''"[[Journal:The modeling of laboratory information systems in higher education based on enterprise architecture planning (EAP) for optimizing monitoring and equipment maintenance|The modeling of laboratory information systems in higher education based on enterprise architecture planning (EAP) for optimizing monitoring and equipment maintenance]]"'''
'''"[[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]]"'''


The [[laboratory]] is a place to conduct scientific [[research]], experiments, measurements, or scientific training. Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Semarang (FMIPA UNNES) has several laboratories distributed in each department to support student lectures. Through the implementation of practicum in the laboratory, students are expected to be able to find a concept, as well as foster scientific attitudes and critical thinking skills. Good laboratory management is expected to be able to utilize laboratory resources effectively and efficiently. [[Scientific instrument|Laboratory equipment]] must be ensured to function properly and be ready to be used for practicum. To support this, it is necessary to [[wikipedia:Condition monitoring|monitor the condition]] of the equipment and immediately repair the equipment if any damage is found. The current obstacle is monitoring tool repairs manually, so there are shortcomings such as poor documentation and equipment conditions that cannot be monitored online ... ('''[[Journal:The modeling of laboratory information systems in higher education based on enterprise architecture planning (EAP) for optimizing monitoring and equipment maintenance|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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