Clustering of the Iranian Asthma and Allergy Specialists' Clinical Information-Seeking Behavior by Neural Network Analysis

The aim of this study was to determine the information retrieval and information therapy behavior of Asthma and allergy specialists in the country, based on cohonen self-organized neural network model.

The methodology of the present study, which is an applied study in terms of purpose, has been done by descriptive-survey method using neural network technique. The tool of this research is a researcher-made questionnaire that was distributed among a sample of people in the community (149 people). After collecting the data, the neural network was selected for data clustering and using MATLAB software version 14, Asthma and allergy specialists were clustered based on the main components of the research. Then, by removing each of the main sub-components of the research, the most effective and least effective option in their information-seeking behavior in working with information resources in this specialized field was determined.

The most effective component in clustering information barriers, was "lack of time due to workload" and the least was "distance of libraries and information centers". About information retrieval skills, the most effective component is "I know what keywords to use when searching the Internet, and I am familiar with synonyms and terms related to the information I need."

By studying the clustering of information behaviors resulting from the information needs of Asthma and allergy specialists, their needs are met, and this is one of the measures that provides the basis for effective research, appropriate findings and, consequently, informational decision-making for those involved in this field.