UMLSKS SUGGEST: an auto-complete feature for the UMLSKS interface using AJAX
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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Anantha Bangalore1, Allen Browne, Guy Divita
1US National Library of Medicine, Bethesda, Maryland, USA.
Abstract:
The idea behind any auto-complete feature is to suggest words or phrases which are likely to complete what the user is typing. The user can then select a suggestion and avoid typing it in full. This feature by all accounts has enhanced the usability of web interfaces. Typically browsers implement this feature by caching a fixed number of queries, previously entered by the user on the client side. Google Suggest (http://ajaxpatterns.org/Suggestion) is an application that replaces a browser's auto-complete feature with one specific to Google searching. Implementing a google suggest like feature requires a large server infrastructure, as basically every time you type a letter, a database is being hit. One of the ways that this feature can be implemented by many applications without access to a large server infrastructure would be to create a small list of suggestions that contains the most likely suggestions for any given application In this poster we describe the methodology used to create a list of suggestions for the UMLS Knowledge Source Server (UMLSKS) interface. We believe that this methodology can be used by any web based application to create a list of suggestions.
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