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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREMWP7030

MEDICAL CHATBOT USING NATURAL LANGUAGE PROCESSING

Stream/Area:

-

Subject:

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Paper ID:

IJSREMWP7030

Volume:

7 |

5 |

May 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

HK

Harsh Kandoi

T

Tharun.K

KR

K.Rajeswara Reddy

DK

Dr.Saravana Kumar

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Abstract

Medical chatbots using AI and ML are emerging as a promising solution for improving healthcare delivery. These chatbots use natural language processing (NLP) algorithms to understand and respond to patients’ queries in real-time. The chatbots can also provide personalized health advice, recommend suitable treatments, and even make appointments with doctors. AI and ML-based chatbots can analyze vast amounts of medical data, including patients’ medical history, symptoms, and treatment outcomes, to provide more accurate diagnoses and treatment options. The chatbots can also detect potential health risks and alert patients to take preventive measures. One of the key benefits of medical chatbots is their ability to provide 24/7 access to healthcare advice and support. This can be especially valuable for people living in remote areas or those with mobility issues. Chatbots can also reduce the burden on healthcare professionals by providing triage and basic care information to patients. Overall, medical chatbots using AI and ML have the potential to transform the healthcare industry by improving patient outcomes, reducing costs, and increasing access to care. However, it is important to ensure that these chatbots are developed with a focus on patient privacy, security, and ethical considerations.

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Cite This Article

Harsh Kandoi, Tharun.K, K.Rajeswara Reddy, Dr.Saravana Kumar, "MEDICAL CHATBOT USING NATURAL LANGUAGE PROCESSING," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 5, May 2023.

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4/5/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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