Bhavana, N and Susmitha, P (2025) Machine Learning Healthcare Chatbot using Python. International Journal of Innovative Science and Research Technology, 10 (5): 25may1334. pp. 2930-2939. ISSN 2456-2165
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Abstract
Birth rate in the country has been greatly increased, with advanced improvements in the art of medicine, thereby reducing death rates. But sadly enough, a real statement is an inadequacy of doctors for a developing nation. Any immediate government hospital linked to any city narrates the tale itself, as, for a substantial portion of treatment-related issues, the negative attitude is towards the doctors who sometimes even juggle matters to the extent of patient deaths. The truth is, doctors-the same as any other human being-may commit errors whilst offering treatment that at times can also lead to, not very simply put, the death of the patient. With the emergence of intelligent and smart chat bots created for advising both patients and physicians, many situations could be solved. It can save the lives of many. There are many potential applications of virtual assistants and chatbots to assist in matters related to medicine in general for patients and health care providers. A chat bot is basically an application program for communication between man and man, usually by text message, applications, or instant messaging. Bots may identify symptoms and give a rough diagnosis depending on the specific pathophysiology while referring them to the best doctor for quick turnaround. The fact that these virtual agents are already being used extensively by other industries such as retail to spruce up their processes means that the escalation of this technology to health care services is surely going to amount to an advantage.
Item Type: | Article |
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Subjects: | T Technology > T Technology (General) |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
Depositing User: | Editor IJISRT Publication |
Date Deposited: | 19 Jun 2025 10:29 |
Last Modified: | 19 Jun 2025 10:29 |
URI: | https://eprint.ijisrt.org/id/eprint/1267 |