Everyone is talking about eHealth, with the NBN on its way. And as usual, no-one is doing anything about it. Well, IBM are. So, I thought I would spend some time coding an experimental demonstration that shows, and discusses some of the subjects considered as part of the eHealth bag of goods that is about to transform the world.
eHealth, associated Life Sciences and Bioinformatics applications are generally multi-server dependants and will have to communicate with several information repositories to carry out any analysis. These applications remain computationally intensive and time consuming as they engage lots of data transfer. Hence they face a major bottleneck when ported as web applications. Browser based web applications normally feature the classical request-response approach. If the response becomes late, as it is expected to happen in the case of long running Diagnostic or Bioinformatics programs, Apache (IE) may get tired and a request timeout error might occur. Alternate approaches like Client-Pull models that involve polling strategy with the unpredictable amount of page refreshes, only tend to intensify the network traffic. Hence a technology that is intelligent enough to support the varied exhaustive Bioinformatics processes becomes highly essential. In this web application, we propose how AJAX can afford a laconic framework within the eHealth applications to reduce the page refresh nuisance and provide a better user experience.
Number crunching and data storage and modelling has been going on for some time. We are experiencing the start of an increase in the application of Biomedical Informatics.
From Wiki: Biomedical informatics is the broad discipline concerned with the study and application of computer science, information science, informatics, cognitive science and human-computer interaction in the practice of biological research, biomedical science, medicine and healthcare. Other fields, including bioinformatics, translational research informatics, clinical research informatics, clinical informatics and public health informatics, medical informatics are commonly cast as sister domains of or subdomains within biomedical informatics .
It was inevitable the life sciences and computer science would become close allies in both research and operation. Both can be data hungry, both make heavy use of statistical method.
The techniques described can be transported to other research or commercial systems.
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