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Title An Adaptive Doctor Recommender System

Author(s) Muhammad Waqar

Abstract Recommender systems apply machine learning techniques to predict about items. These systems are very effective in filtering large amount of information into more concrete form. Due to their effectiveness, they are now been used extensively in approximately all domains. Medical field is one of the domain where a lot of research is going on regarding recommender system utility. The information related to healthcare, available online, has increased tremendously in last few years. Patients now-a-days are more conscious and look to find answers related to healthcare problems online. This resulted in need of a reliable online doctor recommender system which can recommend physicians best suited to a particular patient..In this paper we propose a hybrid doctor recommender system by combining different recommendation approaches i.e. content base filtering, collaborative filtering and demographic filtering. This research work propose a novel adoptive algorithm which is used to construct a doctor’s ranking function. This ranking function can be used to rank doctors according to patient’s requirement. Ranking function is been used to convert patient’s criteria for doctor’s selection into number base rating. This rating is then used for doctor recommendation. We have evaluated our system utility and results show that our system performance is very effective and quite accurate.

Type Thesis/Dissertation MS

Faculty Engineering and Computer Science

Department Engineering

Language English

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