Automatic health recommender systems

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 The amount of data now available makes it extremely difficult to find what we need. While search engines can give relevant information based on content or keywords, they are nevertheless limited by the user's ability to search for relevant information. However, computers can improve recommendations for users by monitoring their activity and interests and proactively presenting relevant content to various persons.Every day, hundreds of new stories are published in the news sector. However, due to space constraints, only a few of them are featured on the website's home page, and users are bound to miss their preferred material due to their various visiting times. A reliable recommendation system can track a user's behaviour and visits and display relevant content to that user. With a huge collection of articles that have a lengthy shelf life in the field of business news, the recommendation system can make outdated information available to the right user based on his interests and reading patterns.

 

One of the more difficult recommendation tasks is recommending news articles. In some aspects, the news domain differs from other domains. The user's interest shifts throughout time and is influenced by a range of external factors. To the extension of this Social networking sites RS plays a key role in Automatic Health Recommender Systems. The majority of the time, people lack the necessary knowledge of hospitals, doctors, and their fields of expertise to choose the right facility and physician for their unique medical issue. The project's objective is to provide a platform for big data analysis that will enable consumers to receive relevant information about hospitals and doctors based on their profiles and dynamic changes. Additionally, the suggested framework calls for sending consumers proactive SMS, email, or advertisement reminders regarding the need for upcoming physicals as well as dynamic generic information appropriate for their health profile. Users of the Automatic Recommender System for Health Care can access services for health information. The system will contain user profiles with updated demographic and health information that users can access. The system will give users information proactively based on their profile as well as in response to their question. Depending on the user's health issue, the system will offer pertinent information on hospitals and doctors.

The system would inform users about routine actions, which may be based on their profiles, such as specific medical exams, immunisations, age-related disorders, etc., via email, SMS, and Ad Post. Users will be asked to rate the hospitals and doctors, and these ratings will be made publicly available to users to help them with decision-making. Through additional methods and video lectures, first aid knowledge will be made available. Alerts will be sent via SMS, email, or advertisement post regarding free check-ups, age-specific diseases, and immunisation requirements for child care. In order to increase user satisfaction, new features will be added to the system over time. Finally, the feature of diet recommendation is also added to the system because many users may obtain health-related information if they obtain diet-related information that will be helpful to the user. since diet is now a major factor in all health-related problems.

Dr. Latha Banda

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