Brainy Diabetes Diagnosis and Doctor Recommendation System
M.Rithvik1, T. Nagaraju2, A. Kalyan Kumar3
1M.Rithvik, Assistant Professor, Srk Institute Of Technology, Enikapadu, Vijayawada.
2T. Nagaraju, Assistant Professor, Srk Institute Of Technology, Enikapadu, Vijayawada.
3Kalyan Kumar, Assistant Professor , Srk Institute Of Technology, Enikapadu, Vijayawada.
Manuscript received on November 25, 2019. | Revised Manuscript received on December 08, 2019. | Manuscript published on December 30, 2019. | PP: 172-175 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3124129219/2019©BEIESP | DOI: 10.35940/ijeat.B3124.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Diabetes is the most common disease that is prevailing now a days from old age people to the young dynamic people which leads to death of the individuals. Eventhough many people are going to hospital in search of a treatment. These treatments may vary from hospital to hospital for the check up and diagnosis. In this scenario there is a need to make people aware of the primitive measures of diabetes and also the treatments as well as the disease intensity stages. This means there should be a treatment from home but not without the presence of a doctor. This paper resembles the diabetes diagnosis system for type1 and type2 diabetes. With the advent of artificial intelligence things are coming to the door steps. This paper illustrates an upcoming technology that makes the finger print based diabetes test system and generation of reports directly to the doctors. As this is the upcoming technology the base of Artificial Intelligence applications in attaining the application of algorithms like SVM, Linear model and Random Classifier.
Keywords: Linear regression, diagnosis, machine learning, Support Vector Machine.