A CHATBOT APPLICATION WITH VOICE COMMUNICATION FOR THE HEALTHCARE SYSTEM
Article Sidebar
Main Article Content
Abstract
The increasing demands of patient care necessitate innovative solutions to alleviate the workload on healthcare providers. One such solution is the implementation of chatbots to address common patient inquiries before intervention by medical staff. This paper presents a chatbot system designed to enhance patient interactions by leveraging the question-answering capabilities of the Llama 3 open-source artificial intelligence (AI) model. Llama 3 plays a central role in generating accurate and contextually appropriate responses from stored data, ensuring that patients receive timely and relevant information. Voice communication between the chatbot and users is facilitated, with a focus on the seamless integration of Llama’s advanced artificial intelligence question-answer function. Chainlit is utilized to create an intuitive interface, further optimizing patient-system interactions. This study outlines the development, integration, and evaluation of the chatbot system within a hospital environment, demonstrating its effectiveness in reducing the burden on healthcare providers while enhancing patient engagement through voice-based Artificial Intelligence interactions.
Downloads
Article Details
References
Multilingual healthcare chatbot using machine
learning. In: 2021 2nd International Conference
for Emerging Technology (INCET). 21–23
May 2021; Belagavi, India. IEEE; 2021. p.1–6.
https://doi.org/10.1109/INCET51464.2021.9456304.
[2] Rarhi K, Bhattacharya A, Mishra A, Mandal K. Automated medical chatbot. SSRN Electronic Journal.
2017;10. https://doi.org/10.2139/ssrn.3090881.
[3] Atmauswan P, Abdullahi A. Intelligent
chatbot for university information system
using natural language approach. Albukhary
Social Business Journal. 2022;3(6): 59–64.
https://doi.org/10.55862/asbjV3I2a007.
[4] Shinde NV, Akhade A, Bagad P, Bhavsar H,
Wagh SK, Kamble A. Healthcare chatbot
system using artificial intelligence. In: 2021
5th International Conference on Trends in
Electronics and Informatics (ICOEI). 03–05
June 2021; Tirunelveli, India. IEEE; 2021. p.1–8.
https://doi.org/10.1109/ICOEI51242.2021.9452902.
[5] Dammavalam SR, Chandana N, Rao TR, Lahari
A, Aparna B. AI based chatbot for hospital
management system. In: 2022 3rd International
Conference on Computing, Analytics and
Networks (ICAN). 18–19 November 2022;
Rajpura, Punjab, India. IEEE; 2022. p.1–5.
https://doi.org/10.1109/ICAN56228.2022.10007105.
[6] Baotravinh. Tra Vinh University Hospital: Gradually
Enhancing the Quality of Medical Examination and
Treatment [Bệnh viện Trường Đại học Trà Vinh:
Từng bước nâng cao chất lượng khám, chữa bệnh].
https://www.baotravinh.vn/xa-hoi/benh-vien-truongdai-hoc-tra-vinh-tung-buoc-nang-cao-chat-luongkham-chua-benh-27005.html. [Accessed 1st May
2024].
[7] Google. Turn speech into text using Google
AI. https://cloud.google.com/speech-to-text?hl=en
[Accessed 20th April 2024].
[8] Google. Text-to-Speech AI.
https://cloud.google.com/text-to-speech?hl=vi
[Accessed 30th April 2024].
[9] Qdrant. Introduction Qdrant.
https://qdrant.tech/documentation/overview
[Accessed 21st April 2024].
[10] Meta. Llama 3 Cheat Sheet: A Complete Guide
for 2024. https://www.techrepublic.com/article/whatis-llama-3. [Accessed 30th April 2024].
[11] Meta. Welcome Llama 3 - Meta’s new open LLM.
https://huggingface.co/blog/llama3 [Accessed: 30th
April 2024].
[12] Meta. Introducing Meta Llama 3: The most
capable openly available LLM to date.
https://ai.meta.com/blog/meta-llama-3 [Accessed
30th April 2024].
[13] Hugging Face. What is Hugging Face?
https://www.techtarget.com/whatis/definition/HuggingFace [Accessed 30th April 2024].
[14] Chainlit. Overview. https://docs.chainlit.io/getstarted/overview [Accessed 1st May 2024].
[15] Hugging Face. Vietnamese-sbert.
https://huggingface.co/keepitreal/vietnamese-sbert
[Accessed 1st May 2024].
[16] Microsoft. Overview of prompts.
https://learn.microsoft.com/en-us/ai-builder/promptsoverview [Accessed 1st May 2024].