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:Fig2 Zheng JPathInfo2015 6.jpg|220px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Huang iScience2022 25-8.jpg|240px]]</div>
'''"[[Journal:Support patient search on pathology reports with interactive online learning based data extraction|Support patient search on pathology reports with interactive online learning based data extraction]]"'''
'''"[[Journal:Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform|Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform]]"'''
 
Structural reporting enables semantic understanding and prompt retrieval of clinical findings about patients. While [[LIS feature#Synoptic reporting|synoptic pathology reporting]] provides templates for data entries, information in [[Clinical pathology|pathology]] reports remains primarily in narrative free text form. Extracting data of interest from narrative pathology reports could significantly improve the representation of the information and enable complex structured queries. However, manual extraction is tedious and error-prone, and automated tools are often constructed with a fixed training dataset and not easily adaptable. Our goal is to extract data from pathology reports to support advanced patient search with a highly adaptable semi-automated data extraction system, which can adjust and self-improve by learning from a user's interaction with minimal human effort. 
 
We have developed an online machine learning based information extraction system called IDEAL-X. With its graphical user interface, the system's data extraction engine automatically annotates values for users to review upon loading each report text. The system analyzes users' corrections regarding these annotations with online machine learning, and incrementally enhances and refines the learning model as reports are processed. ('''[[Journal:Support patient search on pathology reports with interactive online learning based data extraction|Full article...]]''')<br />


One of the top priorities in any [[laboratory]] is [[Archival informatics|archiving]] experimental data in the most secure, efficient, and errorless way. It is especially important to those in chemical and biological research, for it is more likely to damage experiment records. In addition, the transmission of experiment results from paper to electronic devices is time-consuming and redundant. Therefore, we introduce an [[Open-source software|open-source]] no-code [[electronic laboratory notebook]] (ELN), Elegancy, a [[Cloud computing|cloud-based]]/standalone web service distributed as a Docker image. Elegancy fits all laboratories but is specially equipped with several features benefitting biochemical laboratories. It can be accessed via various web browsers, allowing researchers to upload photos or audio recordings directly from their mobile devices. Elegancy also contains a meeting arrangement module, audit/revision control, and laboratory supply management system. We believe Elegancy could help the scientific research community gather evidence, share information, reorganize knowledge, and digitize laboratory works with greater ease and security ... ('''[[Journal:Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform|Full article...]]''')<br />
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Latest revision as of 17:08, 10 April 2023

Fig1 Huang iScience2022 25-8.jpg

"Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform"

One of the top priorities in any laboratory is archiving experimental data in the most secure, efficient, and errorless way. It is especially important to those in chemical and biological research, for it is more likely to damage experiment records. In addition, the transmission of experiment results from paper to electronic devices is time-consuming and redundant. Therefore, we introduce an open-source no-code electronic laboratory notebook (ELN), Elegancy, a cloud-based/standalone web service distributed as a Docker image. Elegancy fits all laboratories but is specially equipped with several features benefitting biochemical laboratories. It can be accessed via various web browsers, allowing researchers to upload photos or audio recordings directly from their mobile devices. Elegancy also contains a meeting arrangement module, audit/revision control, and laboratory supply management system. We believe Elegancy could help the scientific research community gather evidence, share information, reorganize knowledge, and digitize laboratory works with greater ease and security ... (Full article...)

Recently featured: