Modelling Health Recommender System using Hybrid Techniques

From ISLAB/CAISR
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,
TimeFrame
References
Prerequisites Completed courses in basic machine learning are required.
Author
Supervisor Hassan Mashad Nemati, Rebeen Hamad
Level Master
Status Ongoing

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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.