Design and Development of Healthchat

Abstract

A medical chatbot is an essential tool in modern healthcare, providing immediate, accessible support for patients. It aids in symptom assessment, health information dissemination, and appointment scheduling, thereby improving patient engagement and reducing the burden on healthcare providers. Its importance lies in enhancing healthcare accessibility, streamlining workflows, and potentially identifying health issues early, making it a crucial asset in today\'s technology-driven medical landscape. We have created a browser for people to chat and realise their medication or acknowledge their symptoms.

Introduction

I. INTRODUCTION

A chatbot is an AI-powered software application designed to simulate human conversation through text or voice interactions. Utilizing natural language processing (NLP), chatbots can understand and respond to user queries in real-time, making them valuable tools for customer service, information retrieval, and various automated tasks. They range from simple, rule-based systems to advanced AI-driven models capable of nuanced understanding and complex dialogue. Chatbots are increasingly integrated into websites, messaging apps, and virtual assistants, enhancing user experience by providing instant support, streamlining processes, and offering personalized interactions around the clock. A medical chatbot is an AI-driven digital assistant designed to provide users with reliable health information and support. Utilizing natural language processing and machine learning, these chatbots can engage in real-time conversations, answer medical queries, triage symptoms, and offer preliminary diagnoses based on user input. They serve as accessible, 24/7 tools that enhance patient engagement, streamline communication with healthcare providers, and potentially reduce the burden on medical facilities. By offering personalized advice and managing routine inquiries, medical chatbots help improve healthcare efficiency and patient outcomes while ensuring timely and accurate information delivery.

Our chatbot, is a friendly digital companion designed to assist, inform, and engage. Powered by cutting-edge technology, our chatbot is here to provide you with personalized responses, answer your questions, and help you navigate through various tasks effortlessly. With its natural language processing capabilities and vast knowledge base, interacting with our chatbot is like conversing with a knowledgeable friend.

II. LITERATURE SURVEY

A. Chatbot for medical diagnosis

Ankit Garg et al, 2019- Here, the paper suggested that Chatbot, was based on machine learning which was coded in Python Language. This asked for the general information about the patient, suggested the way to prevent the sickness or require any specific medications

B. Design and Development of Chatbot

Rohit Tamrakar et al, 2022-He said that the first step was to determine the Bot’s purpose. The paper suggested the use of NLP. Then designer must decide between a platform based on rules or NLPs. Natural language bot (NLPs) can understand the context and improve their response to the customer’s inquiry.

C. Healthcare Chatbot System using Artificial Intelligence

Varun Srivastava et al, 2021-The paper suggested the use of AI and chatbot for medical diagnosis for diseases and illness. This chatbot provided diagnosis based on the symptoms we tell. This paper was the base of our project.

D. BERT Based Medical Chatbot: Enhancing Healthcare Communication through Natural Language Understanding

Arun Babu et al, 2024- The paper suggested the use of BERT (BIDIRECTIONAL ENCODER REPRESENTATIONS from TRANSFORMERS). BERT helps by providing precise understanding, accurate response, personalized feedback. Here, the person concluded that BERT was better and was a good programming language.

E. The Development and use of chatbots in public health: Scoping Review

Lee Wilson et al, 2022- The paper suggested the three main objectives of a chatbot, they are: To identify application domains in public health, to identify types of chatbots, to ascertain the methods and methodologies by which chatbots were being evaluated in public health applications.                                           

III. METHODOLOGY

In this work, HealthChat was designed to reply with a quick response for the FAQ’s or even any other problems. In today’s medical field chatbot has become a necessity, to help people learn about their symptoms and also replace doctors for non-emergency diagnosis, making it easier for doctor to concentrate more on their important cases.

First a program was developed with the data input and the answers to them. The program has a database that has all the detailed answers/solutions for the queries of user. The program was made using if-else conditional statements. Furthermore, details such as the doctor’s name, their field of expertise and the location of the hospital are added. These were the main data included in the program. The program includes answers to some of the common queries such as:

1. Weight loss
2. Muscle gain
3. Sore throat
4. Fever
5. Ankle sprain, etc.

The program was initially developed in C-Programming initially, but eventually it was ported to Java script since the conversion to Java makes it easier to bring the output on a browser-like interface. Then platform was created with the help of Norde and VS Code. Ensuing the previous step take a folder in VS Code, type 'npx create-react-app, this will initialize the installation of react. React is a front-end framework. Subsequently, front-end was done and to code the program html was used to create the program in VS Code.

Followed by, to design and develop the program, a section in VS Code called CSS Section was used, which also helps in the styling of the program. Second, we have to code the program. We used html to create the program in VS Code.

Successively, the other link shown under the 'code' option inside git app was copied. Then, a folder was opened inside the system and cmd was opened from the same location. 'git clone copied-link' was typed inside cmd and pressed enter. This will enable the installation of all the necessary files into the system which was needed for the program. A folder with all the necessary file was now created inside the folder called 'med'. Comeback to cmd and type in 'npm i'. This will allow all the dependencies to install into the system.

At this stage the program is ready to run. Subsequently, type in 'npm start' inside cmd and the program will open inside (Mozilla Firefox recommended) the default browser. Finally, the Chatbot will open in the browser and the user is able to ask questions to the chatbot.

IV. RESULT AND DISCUSSION

The above image shows the output for a query. It can therefore be said that the chatbot is quick and has access to medical knowledge.

This chatbot also has quite a few merits added to it. Here are the merits:

1. 24/7 Availability: Continuous Support: Medical chatbots provide round-the-clock assistance, ensuring that patients can access healthcare information and support at any time, even outside of regular clinic hours.
2. Enhanced Patient Engagement: Personalized Interaction: By offering tailored responses and reminders, chatbots can engage patients more effectively, improving adherence to treatment plans and promoting healthier lifestyles.
3. Cost-Effectiveness: Reduced Operational Costs: Chatbots can handle a significant portion of patient inquiries and routine tasks, which helps reduce the workload on healthcare professionals and cuts operational costs.
4. Immediate Access to Information: Quick Answers: Patients can get instant answers to their queries about symptoms, medications, and general health advice, which helps in alleviating anxiety and providing immediate guidance.
5. Efficient Triage and Symptom Checking: Preliminary Assessment: Chatbots can perform initial assessments of symptoms and suggest whether a patient needs to see a doctor, visit an emergency room, or manage their condition at home, thus streamlining the triage process.
6. Data Collection and Monitoring: Patient Data Tracking: By interacting with patients, chatbots can collect valuable data regarding symptoms, treatment responses, and overall health trends, which can be used to enhance patient care and conduct medical research.
7. Improved Accessibility: Broad Reach: Especially beneficial for individuals in remote or underserved areas, chatbots can provide medical information and support to those who might have limited access to healthcare facilities.
8. Scalability: Handling Large Volumes: Chatbots can manage a high volume of patient interactions simultaneously without compromising the quality of service, making them highly scalable solutions for healthcare providers.
9. Privacy and Confidentiality: Secure Interactions: Many medical chatbots are designed to comply with healthcare regulations like HIPAA, ensuring that patient interactions remain confidential and secure.
10. Educational Resource: Health Literacy: Chatbots can serve as educational tools, providing patients with reliable health information and helping to improve overall health literacy.

Conclusion

The development and implementation of our medical chatbot signify a significant advancement in healthcare technology, underscoring the potential for artificial intelligence to transform patient care. This project demonstrated that a well-designed chatbot can effectively assist in symptom assessment, provide reliable health information, and facilitate appointment scheduling, thereby enhancing patient engagement and accessibility to healthcare services. Through rigorous design and iterative testing, our chatbot was optimized to understand and respond to a wide range of medical inquiries, offering users immediate support and guidance. The chatbot\'s ability to provide 24/7 assistance addresses the critical need for timely medical information, particularly in situations where access to healthcare professionals is limited. By integrating natural language processing, the chatbot not only enhances user experience but also continuously improves its responses through interaction. However, the project also highlighted several areas for future improvement. Ensuring the accuracy and reliability of the chatbot\'s medical advice remains paramount. Continuous updates and integration with medical databases are necessary to maintain current and precise information. Furthermore, addressing privacy and security concerns is crucial to gaining user trust and complying with healthcare regulations. In conclusion, the medical chatbot project showcases the transformative potential of AI in healthcare. While there are challenges to overcome, the benefits in terms of accessibility, efficiency, and patient engagement are substantial. Continued development and refinement of this technology promise to further bridge the gap between patients and healthcare services, paving the way for a more responsive and connected healthcare system.

References

[1] Ankit Garg et al, “Chatbot for medical diagnosis”, volume: 02, issue: 03, IRJET 2019 [2] Rohit Tamrakar et al, “Design and Development of Chatbot: National Institute of Technology”, volume: 05, issue: 03, published Year 2022 [3] Aafiya Shaikh et al, “A Survey Paper on Chatbots”, volume: 06, issue: 04, published April 2021 [4] Varun Srivastava et al, “Healthcare Chatbot System using Artificial Intelligence”, IRJET volume: 8, issue 1, published on June 2021. [5] Arun Babu et al, “BERT Based Medical Chatbot: Enhancing Healthcare Communication through Natural Language Understanding”, Science Direct volume: 13, published on March 2024. [6] Sophia Keyner et al, “Open Data Chatbot”, Science Direct volume: 1, published on March 2022. [7] Vajinepalli Sai Harsha Vardhan, “Rule Based Chatbot”, IRJET Volume:04, Issue:05, May 2022. [8] Jeya Amantha Kumar, “Educational chatbots for project-based learning: investigating learning outcomes for a team-based design course”, International Journal of Educational Technology in Higher Education, Volume:06, 2021. [9] Lee Wilson et al, “The development and use of chatbots in public health: scoping review”, JMIR, Volume:9, No:4, October 2022. [10] E. Sankar et al, “Building a smart chatbot”, IJCRT, Volume:11, Issue: 05, May 2023.

Copyright

Copyright © 2024 Ms. P. Divya Jenifar, Veeradharshini. R, Vikram Venugopal Iyer, Saheer Mohammed, Venkatachalam. K. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.