Modelling Health Recommender System using Hybrid Techniques
|Title||Modelling Health Recommender System using Hybrid Techniques|
|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|
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.