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A.I. Based Home Doctor

Anuraj Deep, HS. Harshitha, Amratya Singh, R. Kuber, R. Paramesh


Artificial Intelligence (AI) will usher in a new age in medical research. However, currently existing AI systems do not interact with patients, such as for anamnesis, and are thus solely utilized by doctors to make diagnostic or prognosis predictions. These systems, on the other hand, are frequently utilized, for example, in illness or cancer prediction. We created an AI that can engage with a patient in the current study (virtual doctor) by employing a voice recognition and speech synthesis technology, and therefore communicate with the patient autonomously, which is especially essential in rural regions where access to basic medical care is severely limited. T2DM is a noninvasive sensor and deep neural network-based system. Furthermore, the method gives a simple-to-understand likelihood estimate for T2DM for a specific patient. Aside from AI development, we looked at young people's acceptance of AI in healthcare to predict the influence of such a system in the future.


Chatbot, Natural Language Processing, Med Bot, Disease Prediction.

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Deep Learning Techniques for Implementation of Chatbots” Dr.B.Santhosh Kumar, Satyendra Praneel Reddy Karri (2020 International Conference on Computer Communication and Informatics (ICCCI - 2020), Jan. 22 – 24, 2020, Coimbatore, INDIA)

“Automatized Medical Chatbot (Medibot)” Prakhar Srivastava (2020 International Conference on Power Electronics & IoT Applications in Renewable Energy and its Control (PARC))

“Disease Prediction and Treatment Recommendation using Machine Learning” Rohit Binu Mathew, Sandra Varghese, Sera Elsa Joy, Swanthana Susan Alex (Proceedings of the Third International Conference on Trends in Electronics and Informatics (ICOEI 2019) IEEE)

“A Chatbot for Medical Android App” Mrs. Rashmi Dharwadkar, Dr.Mrs. Neeta A. Deshpande (International Journal of Computer Trends and Technology (IJCTT) V60(1):41-45 , June 2018)

“A dialogue monitoring scheme for a virtual doctor” Stavros Mallios, Nikolaos Bourbakis (2015 National Aerospace and Electronics Conference (NAECON)) Shawar, BA and Atwell, E (2002) A comparison between Alice and Elizabeth Chatbot systems. The University of Leeds, School of Computing research report 2002.19.

Informatica 31 (2007) 249-268 249 Supervised Machine Learning: A Review of Classification Techniques S. B. Kotsiantis Department of Computer Science and Technology University of Peloponnese, Greece End of Karaiskaki, 22100, Tripolis GR.

TutorBot: An Application AIML-Based for Web- Learning.”Advanced Technology for Learning (Discontinued) 2005, ACTA Press, Jan. 2000.

De Gasperis, G. (2010). Building an AIML Chatter Bot Knowledge-Base Starting from The FAQ and a Glossary. Journal of e-Learning and Knowledge Society, 6(2), 75-83. Italian e-Learning Association. Retrieved November 20, 2017.

Kurian, Ciji Pearl, and George, V I and Bhat, Jayadev and Aithal, Radhakrishna S (2006) ANFIS Model for the Time Series Prediction of Interior Daylight Illuminance. International Journal on Artificial Intelligence and Machine Learning, 6 (3). pp. 35-40. ISS


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