Online Healthcare Medium for Disease-Treatment using Modified ANN based Classification and Ranking
Mamatha Balipa1, Balasubramani R.2

1Mamatha Balipa*, Department of MCA, NMAM Institute of Technology, Nitte, Karkala, Udupi, Karnataka, India.
2Dr. Balasubramani R., Department of ISE, NMAM Institute of Technology, Nitte, Karkala, Udupi, Karnataka, India.
Manuscript received on January 21, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 29, 2020. | PP: 4029-4036 | Volume-9 Issue-3, February 2020. | Retrieval Number:  C6535029320/2020©BEIESP | DOI: 10.35940/ijeat.C6535.029320
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: The fundamental purpose of the healthcare information medium in social networks is centered on ascertaining the opinions of several people regarding specific user queries. In the backdrop of ever-increasing accessibility and attractiveness of the opinion-rich resources as evidenced by the online review sites and personal blogs, the emerging opportunities and challenges dynamically make use information technologies to go in for and to comprehend the outlook of the vast majority of users. However, it is unfortunate that the time-honored finds its waterloo in locating the impending issue of deploying internet with a view to identify and generate appropriate conclusions regarding the specified ailments. The current investigation effectively carries out the function of processing the user query with the able assistance of the MedHelp website and subsequently forwards the pertinent traits to the sentiwordnet for performing the sentimental examination. It is followed by the creation of the score in accordance with the positivity and negativity of the content in the website. In this regard, the Artificial Neural Network (ANN) is ably guided with the aim of creating rank for the websites. And the weight optimization for ANN is elegantly executed by the efficient Grasshopper Optimization Algorithm (GOA). The technique is performed on the powerful platform of JAVA and the consequent outcomes assessed exhibits incredible decrease in the error rate.
Keywords: User query, Sentiwordnet, Artificial Neural Network(ANN), Grasshopper Optimization Algorithm(GOA), Error rate.