Review on Early Heart Disease Prediction Chatbot using Machine Learning Algorithms

Year : 2024 | Volume :01 | Issue : 02 | Page : 26-33
By

    Tahir Naquash

  1. Pheba Jorson

  2. Ruqsana Khanum

  3. Ruth Hepzibah

  4. S. Niveditha

  1. Assistant Professor, Department of Computer Science Engineering HKBK College of Engineering, Karnataka, India
  2. Student, Department of Computer Science Engineering HKBK College of Engineering, Karnataka, India
  3. Student, Department of Computer Science Engineering HKBK College of Engineering, Karnataka, India
  4. Student, Department of Computer Science Engineering HKBK College of Engineering, Karnataka, India
  5. Student, Department of Computer Science Engineering HKBK College of Engineering, Karnataka, India

Abstract

A chatbot that is developed for the detection of Heart Disease plays an important role in the medical field as it provides the accessible and immediate preliminary assessments. It conducts the screening of individuals efficiently for present or potential heart issues. It also identifies the risk factors associated with the particular condition, contributing to a comprehensive health awareness. Other than delivering early warnings it also offers online monitoring and emergency assistance creating a proactive approach to heart health. Integration with health records enables continuous data collection and ensures per- sonalized care. By using these advanced features the chatbot becomes a tool for the management, prevention, patient education enhancement, improvement of public health and the reduction of healthcare costs by detecting the disease early and helping in intervention. These benefits make it an indispensable asset in the battle against Heart Diseases. The chatbot becomes a versatile tool in the healthcare industry by leveraging advanced functionalities. Supporting public health initiatives and reducing healthcare costs, it improves patient education, promotes prevention, and helps with management. Its capacity to identify illnesses at an early stage and enable interventions makes it crucial in the fight against heart disorders. By means of prompt detection, it facilitates preemptive actions, which may prevent serious consequences.

Keywords: Chatbot, Heart Disease, Dialogflow, Ngrok, Sup- port Vector Machine Algorithm.

[This article belongs to Emerging Trends in Personalized Medicines(etpm)]

How to cite this article: Tahir Naquash, Pheba Jorson, Ruqsana Khanum, Ruth Hepzibah, S. Niveditha , Review on Early Heart Disease Prediction Chatbot using Machine Learning Algorithms etpm 2024; 01:26-33
How to cite this URL: Tahir Naquash, Pheba Jorson, Ruqsana Khanum, Ruth Hepzibah, S. Niveditha , Review on Early Heart Disease Prediction Chatbot using Machine Learning Algorithms etpm 2024 {cited 2024 Mar 29};01:26-33. Available from: https://journals.stmjournals.com/etpm/article=2024/view=136054


References

  • Mehmood A, Iqbal M, Mehmood Z, Irtaza A, Nawaz M, Nazir T, Masood M. Prediction of heart disease using deep convolutional neural networks. Arabian Journal for Science and Engineering. 2021 Apr;46(4):3409-22.
  • Rani P, Kumar R, Ahmed NM, Jain A. A decision support system for heart disease prediction based upon machine learning. Journal of Reliable Intelligent Environments. 2021 Sep;7(3):263-75.
  • Kumari PS, Vinitha S. Heart Attack Prediction in Machine Learning Environment.
  • Atmadjaja A, Nurhadi S, Wartiningsih M. Effectiveness of Chatbot to Reduce the Risk of Coronary Heart Disease using Android-based application.
  • Ruqiya M, Yaqoob MT, Khan AM, Shaikh AA, Khan N. Review on Cleveland Heart Disease Dataset using Machine Learning. Quaid-E-Awam University Research Journal of Engineering, Science & Technology, Nawabshah.. 2023 Jun 30;21(01):87-98.
  • Dhumal PP, Kavthale PP, Sonawane V. Cardiovascular Disease Prediction System.
  • CHANDRASEKARAN A, KALLA D. Heart disease prediction using chi-square test and linear regression. Computer Science & Information Technology. 2023;13:135-46.
  • Lunugalage D, Jayanetti P, Mahawatta ID, Amarasingha KG. Heart to Heart: application: Predicting presence of heart diseases using machine learning techniques. ResearchGate. 2021 Oct.
  • Dharwadkar R, Deshpande NA. A medical chatbot. International Journal of Computer Trends and Technology (IJCTT). 2018 Jun;60(1):41-5.
  • Divya S, Indumathi V, Ishwarya S, Priyasankari M, Devi SK. A self-diagnosis medical chatbot using artificial intelligence. Journal of Web Development and Web Designing. 2018 Apr;3(1):1-7.
  • Gratzer D, Goldbloom D. Therapy and e-therapy—preparing future psychiatrists in the era of apps and chatbots. Academic Psychiatry. 2020 Apr;44:231-4.
  • Patil MV, Shree P, Singh P. AI based healthcare chat bot system. International Journal of Scientific & Engineering Research. 2021 Jul 25;12(7).
  • Jayashree K, Monika KA, Preetha R, Piraisoodan SP. The Smart Health Care Prediction using Chatbot. International Journal of Recent Technology and Engineering (IJRTE). 2020;9(2):75-8.
  • Bhirud N, Tataale S, Randive S, Nahar S. A literature review on chatbots in healthcare domain. Int J Sci Technol Res. 2019 Jul;8(7):225-31.
  • Omarov B, Zhumanov Z, Gumar A, Kuntunova L. Artificial Intelligence Enabled Mobile Chatbot Psychologist using AIML and Cognitive Behavioral Therapy. International Journal of Advanced Computer Science and Applications. 2023;14(6).
Regular Issue Subscription Review Article
Volume 01
Issue 02
Received March 20, 2024
Accepted March 25, 2024
Published Mar 29, 2024
Views: 44