Modelling Health Recommender System using Hybrid Techniques

Title	Modelling Health Recommender System using Hybrid Techniques
Summary	The goal of this project to develop a health recommender system using existing machine learning techniques.
Keywords	Recommendation system, Machine learning, Expert system,Property "Keywords" has a restricted application area and cannot be used as annotation property by a user.
TimeFrame
References
Prerequisites	Completed courses in basic machine learning are required.
Author
Supervisor	Hassan Mashad Nemati, Rebeen Hamad
Level	Master
Status	Ongoing

This project has the purpose of exploring the use of existing AI methods and machine learning algorithms for health data assessment in order to develop build a recommender system. The primary goal is to plan, develop and test a knowledge-base of health recommendations to be used for automation, increased health and performance. Our methodology for building the Diagnostics and recommender (D-R) system is sub-divided into three steps: building a model for analyzing the structured data, building a model for extrapolating the unstructured data and then finally a model that correlates them to produce an appropriate recommendation.