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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'''"[[Journal:Making big data useful for health care: A summary of the inaugural MIT Critical Data Conference|Making big data useful for health care: A summary of the inaugural MIT Critical Data Conference]]"'''
'''"[[Journal:Human–information interaction with complex information for decision-making|Human–information interaction with complex information for decision-making]]"'''


With growing concerns that big data will only augment the problem of unreliable research, the Laboratory of Computational Physiology at the Massachusetts Institute of Technology organized the Critical Data Conference in January 2014. Thought leaders from academia, government, and industry across disciplines — including clinical medicine, computer science, public health, [[informatics]], biomedical research, health technology, statistics, and epidemiology — gathered and discussed the pitfalls and challenges of big data in health care. The key message from the conference is that the value of large amounts of data hinges on the ability of researchers to share data, methodologies, and findings in an open setting. If empirical value is to be from the analysis of retrospective data, groups must continuously work together on similar problems to create more effective peer review. This will lead to improvement in methodology and quality, with each iteration of analysis resulting in more reliability. ('''[[Journal:Making big data useful for health care: A summary of the inaugural MIT Critical Data Conference|Full article...]]''')<br />
Human–information interaction (HII) for simple [[information]] and for complex information is different because people's goals and information needs differ between the two cases. With complex information, comprehension comes from understanding the relationships and interactions within the information and factors outside of a design team's control. Yet, a design team must consider all these within an HII design in order to maximize the communication potential. This paper considers how simple and complex information requires different design strategies and how those strategies differ. ('''[[Journal:Human–information interaction with complex information for decision-making|Full article...]]''')<br />


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''Recently featured'': [[Journal:Beyond information retrieval and electronic health record use: Competencies in clinical informatics for medical education|Beyond information retrieval and electronic health record use: Competencies in clinical informatics for medical education]], [[Journal:Analyzing huge pathology images with open source software|Analyzing huge pathology images with open source software]], [[Journal:iLAP: A workflow-driven software for experimental protocol development, data acquisition and analysis|iLAP: A workflow-driven software for experimental protocol development, data acquisition and analysis]]
''Recently featured'': [[Journal:Making big data useful for health care: A summary of the inaugural MIT Critical Data Conference|Making big data useful for health care: A summary of the inaugural MIT Critical Data Conference]], [[Journal:Beyond information retrieval and electronic health record use: Competencies in clinical informatics for medical education|Beyond information retrieval and electronic health record use: Competencies in clinical informatics for medical education]], [[Journal:Analyzing huge pathology images with open source software|Analyzing huge pathology images with open source software]]

Revision as of 16:05, 26 October 2015

Fig1 Albers Informatics2015 2-2.jpg

"Human–information interaction with complex information for decision-making"

Human–information interaction (HII) for simple information and for complex information is different because people's goals and information needs differ between the two cases. With complex information, comprehension comes from understanding the relationships and interactions within the information and factors outside of a design team's control. Yet, a design team must consider all these within an HII design in order to maximize the communication potential. This paper considers how simple and complex information requires different design strategies and how those strategies differ. (Full article...)


Recently featured: Making big data useful for health care: A summary of the inaugural MIT Critical Data Conference, Beyond information retrieval and electronic health record use: Competencies in clinical informatics for medical education, Analyzing huge pathology images with open source software