Knowledge based Medical Decision Support System using Data Mining
Taranath N L1, Roopashree H R2, Yogeesh A C3, Subbaraya C K4, Darshan L M5

1Taranath N L*, Dept. Of CS & E, AIT, Chikkamagaluru, Karnataka.
2Roopashree H R, Dept. of CS & E, GSSITEW, Mysuru, Karnataka.
3Yogeesh A C, Dept. of CS & E, GEC, Kushalnagar, Karnataka.
4Subbaraya C K, Registrar, Adichunchanagiri University, BG Nagara, Karnataka.
5Darshan L M, Dept. of CS & E, AIT, Chikkamagaluru, Karnataka.

Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 5350-5355 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4240119119/2019©BEIESP | DOI: 10.35940/ijitee.A4240.119119
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Abstract: Medical Decision Support System (MDSS)[7] is a system where information of the patient for1promising1diagnostic and1treatment paths are depicted. It can1be developed either1as the system for1Knowledge base or the system for1Learning base[2]. Knowledge-based systems[3] are the mappings which are human-engineered from the best medical practices and patient data recommendations [1]. The mapping is derived by Learning-based systems using various techniques of data mining, machine learning.. Knowledge-based and Learning-based systems are integrated to provide a powerful solution to the information challenge in the existence of incomplete facts. This work designs a framework and implements an ontological representation for Integrated Medical Decision Support System which assists Medical Professionals in making clinical decisions for drug prescription. It employs Knowledge base system for drug prescription to the patients. If the available data is incomplete, it uses concept of machine learning to produce solution for the given query [5]. It is best suited for different healthcare environment and many different users including physicians, nurses and other staff who serve in medical field. The skeleton is query-based which can be adjusted for use with many different interfaces on the user-end including Desktop, Web-based browsers and Mobile applications.
Keywords: MDSS, Knowledge-based systems, Learning based systems, Aggregations, SQL, Data Mining
Scope of the Article: Data Mining