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A Machine Learning-based Healthcare Diagnostic Model

by Prakhar Mittal, Udit Parasher, Ruhi Khanna, Parv Yadav, Sunil Kumar, Mariya Khurshid
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 16
Year of Publication: 2022
Authors: Prakhar Mittal, Udit Parasher, Ruhi Khanna, Parv Yadav, Sunil Kumar, Mariya Khurshid
10.5120/ijca2022922147

Prakhar Mittal, Udit Parasher, Ruhi Khanna, Parv Yadav, Sunil Kumar, Mariya Khurshid . A Machine Learning-based Healthcare Diagnostic Model. International Journal of Computer Applications. 184, 16 ( Jun 2022), 1-4. DOI=10.5120/ijca2022922147

@article{ 10.5120/ijca2022922147,
author = { Prakhar Mittal, Udit Parasher, Ruhi Khanna, Parv Yadav, Sunil Kumar, Mariya Khurshid },
title = { A Machine Learning-based Healthcare Diagnostic Model },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2022 },
volume = { 184 },
number = { 16 },
month = { Jun },
year = { 2022 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number16/32399-2022922147/ },
doi = { 10.5120/ijca2022922147 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:21:33.471272+05:30
%A Prakhar Mittal
%A Udit Parasher
%A Ruhi Khanna
%A Parv Yadav
%A Sunil Kumar
%A Mariya Khurshid
%T A Machine Learning-based Healthcare Diagnostic Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 16
%P 1-4
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This To live a healthy life, healthcare is considered very important but it is terribly difficult to get consultation from a doctor nowadays. The basic idea and motive of the project is to build a chatbot system by using AI (Artificial Intelligence) that can predict the health problems and give details of the disease before consulting the Doctor. The system provides text assistance to coordinate with the chatbot. Based on user’s symptoms chatbot will provide what kind of disease user have and provide doctor’s details according to the diagnose. Based on the symptom that user have chatbot will tell user the disease with all the other possible symptoms. The chat will inform whether the disease is major or minor. Hence, user can gain the maximum benefit of this AI based chatbot only after it diagnoses maximum kinds of illness and provide with all the required information.

References
  1. Dharwadkar, Rashmi, and Neeta A. Deshpande. "Medical chatbot." Int J Comp Trends Technol 60.1 (2018).
  2. Bali, Manish, et al. "Diabot: a predictive medical chatbot that uses integrated learning." Int. J. of Recent Technol. and Eng. (2019): 2277-3878.
  3. Bao, Q., Ni, L. and Liu, J., 2020, February. HHH: an online medical discussion system based on a graph of information and consecutive attention to two categories. At the Australian Computer Science Conference Multiconference (pp. 1-10).
  4. Kalla, D. and Samiuddin, V., 2020. Chatbot treatment using NLTK Lib. IOSR- J. Computer. Engi, 22.
  5. Chung, K. and Park, R.C., 2019. Chatbot-based healthcare service with basic cloud computing knowledge. Cluster Computing, 22 (1), pp.1925-1937.Harilal, N., Shah, R., Sharma, S. and Bhutan, V., 2020. CARO: sympathetic health dialogue for people with major depression. In the 7th ACM
  6. Aswini, D., 2019. Disclosure of medical information using crowdsourcing tech- nique. Int. Res. J. Eng. Technology, 6.
  7. Rarhi, K., Bhattacharya, A., Mishra, A. and Mandal, K., 2017. Automatic medical discussion. Available on SSRN 3090881.
  8. Yoo, S. and Jeong, O., 2020. Intelligent Chatbot Using BERT Model and Information Graph. Journal of the e-Business Studies Organization, 24 (3).
  9. All, S., 2018. “Plutchik”: an artificial intelligence chatbot to search for NCBI databases. Medical Library Association Journal: JMLA, 106 (4), p.501.
  10. Brixey, J., Hoegen, R., Lan, W., Rusow, J., Singla, K., Yin, X., Artstein, R. and Leuski, A., 2017, August. Shihbot: Facebook chatbot for sexual health information on hiv / aids. In discussions of the 18th annual SIGdial meeting on speeches and interviews (pp. 370- 373).
  11. Sophia, J.J., Kumar, D.A., Arutselvan, M. and Ram, S.B., 2020. A survey of the use of chatbot in health care using NLTK. Int. J. Computer. Science. The crowd. Computer, 9.
  12. Zarouali, B., Van den Broeck, E., Walrave, M. and Poels, K., 2018. Predicting customer responses to chatbot on Facebook. Cyberpsychology, Behavior, and Social Networking-, 21 (8), pp.491-497.
  13. Dahiya, M., 2017. Chat tool: Chatbot. International Journal of Computer Science and Engineering, 5 (5), pp.158-161.
  14. https://www.kaggle.com/data/86712
  15. https://www.kaggle.com/pawanyalla/medical
Index Terms

Computer Science
Information Sciences

Keywords

Online Diagnosis Chatbot Healthcare Diseases.

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