View source for Modelling Health Recommender System using Hybrid Techniques

{{StudentProjectTemplate
|Summary=The goal of this project is to develop a health recommender system using existing machine learning techniques.
|Keywords=Recommendation system, Machine learning, Expert system,
|Prerequisites=Completed courses in basic machine learning are required.
|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.