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

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(Updated article of the week text.)
(Updated article of the week text.)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Zheng JMIRMedInfo2017 5-2.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Buabbas JMIRMedInfo2016 4-2.png|240px]]</div>
'''"[[Journal:Effective information extraction framework for heterogeneous clinical reports using online machine learning and controlled vocabularies|Effective information extraction framework for heterogeneous clinical reports using online machine learning and controlled vocabularies]]"'''
'''"[[Journal:Users’ perspectives on a picture archiving and communication system (PACS): An in-depth study in a teaching hospital in Kuwait|Users’ perspectives on a picture archiving and communication system (PACS): An in-depth study in a teaching hospital in Kuwait]]"'''


Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedback for improving the extraction algorithm in real time.
The [[picture archiving and communication system]] (PACS) is a well-known [[imaging informatics]] application in health care organizations, specifically designed for the radiology department. Health care providers have exhibited willingness toward evaluating PACS in hospitals to ascertain the critical success and failure of the technology, considering that evaluation is a basic requirement.


Our goal was to provide a generic [[information]] extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results.
This study aimed to evaluate the success of a PACS in a regional teaching hospital of Kuwait, from users’ perspectives, using information systems success criteria.


A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedback to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. ('''[[Journal:Effective information extraction framework for heterogeneous clinical reports using online machine learning and controlled vocabularies|Full article...]]''')<br />
An in-depth study was conducted by using quantitative and qualitative methods. This mixed-method study was based on: (1) questionnaires, distributed to all radiologists and technologists and (2) interviews, conducted with PACS administrators. ('''[[Journal:Users’ perspectives on a picture archiving and communication system (PACS): An in-depth study in a teaching hospital in Kuwait|Full article...]]''')<br />
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''Recently featured'':  
''Recently featured'':  
: ▪ [[Journal:Effective information extraction framework for heterogeneous clinical reports using online machine learning and controlled vocabularies|Effective information extraction framework for heterogeneous clinical reports using online machine learning and controlled vocabularies]]
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: ▪ [[Journal:Selecting a laboratory information management system for biorepositories in low- and middle-income countries: The H3Africa experience and lessons learned|Selecting a laboratory information management system for biorepositories in low- and middle-income countries: The H3Africa experience and lessons learned]]
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Revision as of 14:19, 26 July 2017

Fig2 Buabbas JMIRMedInfo2016 4-2.png

"Users’ perspectives on a picture archiving and communication system (PACS): An in-depth study in a teaching hospital in Kuwait"

The picture archiving and communication system (PACS) is a well-known imaging informatics application in health care organizations, specifically designed for the radiology department. Health care providers have exhibited willingness toward evaluating PACS in hospitals to ascertain the critical success and failure of the technology, considering that evaluation is a basic requirement.

This study aimed to evaluate the success of a PACS in a regional teaching hospital of Kuwait, from users’ perspectives, using information systems success criteria.

An in-depth study was conducted by using quantitative and qualitative methods. This mixed-method study was based on: (1) questionnaires, distributed to all radiologists and technologists and (2) interviews, conducted with PACS administrators. (Full article...)

Recently featured:

▪ Effective information extraction framework for heterogeneous clinical reports using online machine learning and controlled vocabularies
▪ Selecting a laboratory information management system for biorepositories in low- and middle-income countries: The H3Africa experience and lessons learned
▪ Baobab Laboratory Information Management System: Development of an open-source laboratory information management system for biobanking
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