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

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text.)
(Updated article of the week text.)
 
(464 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Liver cyst wall - high mag.jpg|220px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Signoroni NatComm23 14.png|240px]]</div>
'''[[Histopathology]]''' is a branch of histology and pathology that studies and diagnoses diseases on the tissue and cellular level. While histopathology is closely related to [[cytopathology]], the main difference is diagnostic information gained from histopathology is acquired from solid tissue samples, whereas specific disaggregated cell preparations are used in cytopathology. Typically a biopsy or surgical specimen is examined by a pathologist after the specimen has been processed and histological sections have been placed onto glass slides. Testing typically incorporates several stages, from collection and preparation using numerous methods (depending on the sample and test type) down to examination.
'''"[[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]]"'''


Rudolf Ludwig Karl Virchow is considered by many to be one of the fathers of cellular pathology, remembered most for his collection of lectures on the topic, published as ''Cellular Pathology'' in 1858. However, his assistant, David Paul von Hansemann also played an important role in the progress of histopathology during the 1890s, producing his book ''The Microscopic Diagnosis of Malignant Tumours'' and other important research. ('''[[Histopathology|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 />
<br />
''Recently featured'':
''Recently featured'': [[Clinical chemistry]], [[Desktop virtualization]], [[Comprehensive outpatient rehabilitation facility]]
{{flowlist |
* [[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]
* [[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]
* [[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]
}}

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: