title: Personalized online information search and visualization.
abstract: BACKGROUND
  The rapid growth of online publications such as the Medline and other sources raises the questions how to get the relevant information efficiently. It is important, for a bench scientist, e.g., to monitor related publications constantly. It is also important, for a clinician, e.g., to access the patient records anywhere and anytime. Although time-consuming, this kind of searching procedure is usually similar and simple. Likely, it involves a search engine and a visualization interface. Different words or combination reflects different research topics. The objective of this study is to automate this tedious procedure by recording those words/terms in a database and online sources, and use the information for an automated search and retrieval. The retrieved information will be available anytime and anywhere through a secure web server.
  
  
  RESULTS
  We developed such a database that stored searching terms, journals and et al., and implement a piece of software for searching the medical subject heading-indexed sources such as the Medline and other online sources automatically. The returned information were stored locally, as is, on a server and visible through a Web-based interface. The search was performed daily or otherwise scheduled and the users logon to the website anytime without typing any words. The system has potentials to retrieve similarly from non-medical subject heading-indexed literature or a privileged information source such as a clinical information system. The issues such as security, presentation and visualization of the retrieved information were thus addressed. One of the presentation issues such as wireless access was also experimented. A user survey showed that the personalized online searches saved time and increased and relevancy. Handheld devices could also be used to access the stored information but less satisfactory.
  
  
  CONCLUSIONS
  The Web-searching software or similar system has potential to be an efficient tool for both bench scientists and clinicians for their daily information needs.
authors.affiliation: Biostatistics and Bioinformatics Unit, Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama, USA. dongquan@uab.edu
authors.forename: Dongquan
authors.initials: D
authors.lastname: Chen
authors.forename: Helmuth F
authors.initials: HF
authors.lastname: Orthner
authors.forename: Susan M
authors.initials: SM
authors.lastname: Sell
mesh_terms: D016206:Databases, Bibliographic / Q000706:statistics & numerical data*; D004526:Efficiency; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D016239:MEDLINE / Q000706:statistics & numerical data; D046650:Medical Subject Headings; D016571:Neural Networks, Computer; D009862:Online Systems; D012984:Software; D014584:User-Computer Interface