Authors :
N Bhavana; P Susmitha
Volume/Issue :
Volume 10 - 2025, Issue 5 - May
Google Scholar :
https://tinyurl.com/mrre7xx6
DOI :
https://doi.org/10.38124/ijisrt/25may1334
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
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.
Keywords :
Intelligent Chat Bot, Virtual Assistants, Medical-Related Assignment, Diagnostics, Health Service.
References :
- S. Sai, A. Gaur, R. Sai, V. Chamola, M. Guizani, and J. J. P. C. Rodrigues, “Generative AI for Transformative Healthcare: A Comprehensive Study of Emerging Models, Applications, Case Studies, and Limitations,” IEEE Access, vol. 12, pp. 31078–31106, 2024, doi: 10.1109/ACCESS.2024.3367715.
- I. Almubark, “Exploring the Impact of Large Language Models on Disease Diagnosis,” IEEE Access, 2025, doi: 10.1109/ACCESS.2025.3527025.
- K. Katsaliaki and S. Kumar, “The Past, Present, and Future of the Healthcare Delivery System Through Digitalization,” IEEE Engineering Management Review, vol. 50, no. 4, pp. 21–33, 2022, doi: 10.1109/EMR.2022.3223112.
- Q. U. A. Arshad, W. Z. Khan, F. Azam, and M. K. Khan, “Deep-Learning-Based COVID-19 Detection: Challenges and Future Directions,” IEEE Transactions on Artificial Intelligence, vol. 4, no. 2, pp. 210–228, Apr. 2023, doi: 10.1109/TAI.2022.3224097.
- A. Abdulnazar, R. Roller, S. Schulz, and M. Kreuzthaler, “Large Language Models for Clinical Text Cleansing Enhance Medical Concept Normalization,” IEEE Access, 2024, doi: 10.1109/ACCESS.2024.3472500.
- X. Wu, J. Duan, Y. Pan, and M. Li, “Medical Knowledge Graph: Data Sources, Construction, Reasoning, and Applications,” Big Data Mining and Analytics, vol. 6, no. 2, pp. 201–217, Jun. 2023, doi: 10.26599/BDMA.2022.9020021.
- A. Hoogi, A. Mishra, F. Gimenez, J. Dong, and D. Rubin, “Natural Language Generation Model for Mammography Reports Simulation,” IEEE J Biomed Health Inform, vol. 24, no. 9, pp. 2711–2717, Sep. 2020, doi: 10.1109/JBHI.2020.2980118.
- M. L. Rockoff, “An Overview of Some Technological/Healthcare System Implications of Seven Exploratory Broadband Communication Experiments,” IEEE Transactions on Communications, vol. 23, no. 1, pp. 20–30, 1975, doi: 10.1109/TCOM.1975.1092657.
- L. Liu, J. Xu, Y. Huan, Z. Zou, S. C. Yeh, and L. R. Zheng, “A Smart Dental Health-IoT Platform Based on Intelligent Hardware, Deep Learning, and Mobile Terminal,” IEEE J Biomed Health Inform, vol. 24, no. 3, pp. 898–906, Mar. 2020, doi: 10.1109/JBHI.2019.2919916.
- H. Cao et al., “Barriers and Enablers to the Implementation of Intelligent Guidance Systems for Patients in Chinese Tertiary Transfer Hospitals: Usability Evaluation,” IEEE Trans Eng Manag, vol. 70, no. 8, pp. 2634–2643, Aug. 2023, doi: 10.1109/TEM.2021.3066564.
- Y. Mao and L. Zhang, “Optimization of the Medical Service Consultation System Based on the Artificial Intelligence of the Internet of Things,” IEEE Access, vol. 9, pp. 98261–98274, 2021, doi: 10.1109/ACCESS.2021.3096188.
- A. Ahmed, R. Xi, M. Hou, S. A. Shah, and S. Hameed, “Harnessing Big Data Analytics for Healthcare: A Comprehensive Review of Frameworks, Implications, Applications, and Impacts,” IEEE Access, vol. 11, pp. 112891–112928, 2023, doi: 10.1109/ACCESS.2023.3323574.
- Z. T. Hamad, N. Jamil, and A. N. Belkacem, “ChatGPT’s Impact on Education and Healthcare: Insights, Challenges, and Ethical Consideration,” IEEE Access, vol. 12, pp. 114858–114877, 2024, doi: 10.1109/ACCESS.2024.3437374.
- B. Zhou, G. Yang, Z. Shi, and S. Ma, “Natural Language Processing for Smart Healthcare,” IEEE Rev Biomed Eng, vol. 17, pp. 4–18, 2024, doi: 10.1109/RBME.2022.3210270.
- C. Crema et al., “Medical Information Extraction With NLP-Powered QABots: A Real-World Scenario,” IEEE J Biomed Health Inform, 2024, doi: 10.1109/JBHI.2024.3450118.
- J. Qiu et al., “Large AI Models in Health Informatics: Applications, Challenges, and the Future,” IEEE J Biomed Health Inform, vol. 27, no. 12, pp. 6074–6087, Dec. 2023, doi: 10.1109/JBHI.2023.3316750.
- S. Nasir, R. A. Khan, and S. Bai, “Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond,” IEEE Access, vol. 12, pp. 31014–31035, 2024, doi: 10.1109/ACCESS.2024.3369912.
- K. Katsaliaki and S. Kumar, “The Past, Present, and Future of the Healthcare Delivery System Through Digitalization,” IEEE Engineering Management Review, vol. 50, no. 4, pp. 21–33, 2022, doi: 10.1109/EMR.2022.3223112.
- S. Sai, A. Gaur, R. Sai, V. Chamola, M. Guizani, and J. J. P. C. Rodrigues, “Generative AI for Transformative Healthcare: A Comprehensive Study of Emerging Models, Applications, Case Studies, and Limitations,” IEEE Access, vol. 12, pp. 31078–31106, 2024, doi: 10.1109/ACCESS.2024.3367715.
- X. Ren, G. Spina, S. De Vries, A. Bijkerk, B. Faber, and A. Geraedts, “Understanding Physician’s Experience with Conversational Interfaces during Occupational Health Consultation,” IEEE Access, vol. 8, pp. 119158–119169, 2020, doi: 10.1109/ACCESS.2020.3005733.
- K. A. Kumar, J. F. Rajan, C. Appala, S. Balurgi, and P. R. Balaiahgari, “Medibot: Personal Medical Assistant,” Proceedings of the 2nd IEEE International Conference on Networking and Communications 2024, ICNWC 2024, 2024, doi: 10.1109/ICNWC60771.2024.10537532.
- K. S. Nandini Prasad, S. Sudhanva, T. N. Tarun, Y. Yuvraaj, and D. A. Vishal, “Conversational Chatbot Builder - Smarter Virtual Assistance with Domain Specific AI,” 2023 4th International Conference for Emerging Technology, INCET 2023, 2023, doi: 10.1109/INCET57972.2023.10170114.
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.
Keywords :
Intelligent Chat Bot, Virtual Assistants, Medical-Related Assignment, Diagnostics, Health Service.