Awareness of cancer patients and their families, health care providers, and specialized cancer centers is achieved through access to up-to-date information about various items. Today, intelligent information technology systems have an important role in the awareness of people. Therefore, a type of technology is required that is capable of learning people’s needs, interests and suggesting appropriate information accordingly. The emergence of information technology systems, like recommender systems, is a step towards selecting appropriate information. With modeling the preferences, interests, needs, requests, and behaviors of the users, recommender systems seek to predict the future preferences, needs, and behaviors of the users to recommend appropriate and helpful services accordingly. Recommender systems can be a suitable tool for the information management of cancer-related screenings, diagnoses, treatments, operations, and rehabilitation programs. Access to treatment and health recommendations from valid sources is an important component of the natural processes of human decision making. The aim of this collection is to introduce recommender systems to use in cancer-related issues.
Background: There are many people who are suffering from a variety of physical and mental illnesses due to the chemical attacks. There are various technologies such as recommender systems that can identify the main concerns related to health and make efforts to address them. To design and develop a recommender system, preparation of data source of this system should be considered. The aim of this study was to determine the minimum data set for user profile or user's electronic health record in chemical warfare victims’ recommender system. Methods: This applied descriptive, cross-sectional study which was conducted in 2017. A questionnaire was developed by the authors from the data elements that were collected using the data extraction form from the studied sources. Content validity of the questionnaire was confirmed by using the experts. Test–retest method was used to determine the reliability of the questionnaire. The reliability of the questionnaire with Cronbach's alpha coefficient was confirmed as 84%. The questionnaire were submitted for related experts based on Delphi method by email or in person. Data resulting from the Delphi technique with descriptive statistics methods in SPSS software were analyzed. Results: Forty-seven nonclinical data elements and 181 clinical data elements were classified. Conclusion: Determining minimum data set of user profile or electronic health record in the recommender system for chemical warfare victims helps the health authorities to implement the recommender system which demonstrates chemical warfare victims’ needs.
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