Optimizing Telehealth Services with LILM-Driven Conversational Agents: An HCI Evaluation
DOI:
https://doi.org/10.5281/zenodo.13144268ARK:
https://n2t.net/ark:/40704/JIEAS.v2n4a18Keywords:
Telehealth Services, Large Language Models (LLMs), Conversational Agents, Human-Computer interaction (HCI), Patient Engagement, Healthcare EfficiencyAbstract
Telehealth services have become increasingly important, especially in the wake of global health crises such as the COVID-19 pandemic, offering a necessary alternative to traditional in-person healthcare delivery. However, scalability and efficiency challenges persist due to high demand, limited provider availability, and the need for personalized interactions. This paper explores the use of large language models (LLMs) like OpenAI's GPT-4 as conversational agents within telehealth platforms to address these issues. We evaluate the human-computer interaction (HCI) aspects of LLM-driven agents through controlled experiments and user studies, assessing metrics such as user satisfaction, task completion time, and error rates. Our findings indicate that LLM-driven agents significantly enhance telehealth experiences by providing timely, accurate, and empathetic responses, thereby reducing provider workload and improving patient engagement and satisfaction. Integrating these agents into telehealth platforms offers a promising solution to current challenges, enhancing patient experience and operational efficiency. Future research should address data privacy, ethical considerations, and continuous model updates to ensure reliability and safety.
Downloads
Metrics
References
Yan, H., Xiao, J., Zhang, B., Yang, L., & Qu, P. (2024). The Application of Natural Language Processing Technology in the Era of Big Data. Journal of Industrial Engineering and Applied Science, 2(3), 20-27.
Zhou, Z. (2024, February). ADVANCES IN ARTIFICIAL INTELLIGENCE-DRIVEN COMPUTER VISION: COMPARISON AND ANALYSIS OF SEVERAL VISUALIZATION TOOLS. In The 8th International scientific and practical conference “Priority areas of research in the scientific activity of teachers”(February 27–March 01, 2024) Zagreb, Croatia. International Science Group. 2024. 298 p. (p. 224).
Zhang, B., Xiao, J., Yan, H., Yang, L., & Qu, P. (2024). Review of NLP Applications in the Field of Text Sentiment Analysis. Journal of Industrial Engineering and Applied Science, 2(3), 28-34.
Zhou, J., Liang, Z., Fang, Y., & Zhou, Z. (2024). Exploring Public Response to ChatGPT with Sentiment Analysis and Knowledge Mapping. IEEE Access.
Liu, S., Wu, K., Jiang, C., Huang, B., & Ma, D. (2023). Financial Time-Series Forecasting: Towards Synergizing Performance And Interpretability Within a Hybrid Machine Learning Approach. arXiv e-prints, arXiv-2401.
Zhang, B., Yan, H., Wu, J., & Qu, P. (2024). Application of Semantic Analysis Technology in Natural Language Processing. Journal of Computer Technology and Applied Mathematics, 1(2), 27-34.
Wu, R. (2024). Leveraging Deep Learning Techniques in High-Frequency Trading: Computational Opportunities and Mathematical Challenges. Academic Journal of Sociology and Management, 2(4), 27-34.
Liu, T., Cai, Q., Xu, C., Hong, B., Ni, F., Qiao, Y., & Yang, T. (2024). Rumor Detection with A Novel Graph Neural Network Approach. Academic Journal of Science and Technology, 10(1), 305-310.
Zhou, Z., Xu, C., Qiao, Y., Ni, F., & Xiong, J. (2024). An Analysis of the Application of Machine Learning in Network Security. Journal of Industrial Engineering and Applied Science, 2(2), 5-12.
Xiong, J., Feng, M., Wang, X., Jiang, C., Zhang, N., & Zhao, Z. (2024). Decoding sentiments: Enhancing covid-19 tweet analysis through bert-rcnn fusion. Journal of Theory and Practice of Engineering Science, 4(01), 86-93.
Xiong, J., Jiang, C., Zhao, Z., Qiao, Y., Zhang, N., Feng, M., & Wang, X. (2024). Selecting the Best Fit Software Programming Languages: Using BERT for File Format Detection. Journal of Theory and Practice of Engineering Science, 4(06), 20-28.
Li, K., Zhu, A., Zhou, W., Zhao, P., Song, J., & Liu, J. (2024). Utilizing deep learning to optimize software development processes. arXiv preprint arXiv:2404.13630.
Liu, T., Xu, C., Qiao, Y., Jiang, C., & Chen, W. (2024). News Recommendation with Attention Mechanism. Journal of Industrial Engineering and Applied Science, 2(1), 21-26.
Zhang, N., Xiong, J., Zhao, Z., Feng, M., Wang, X., Qiao, Y., & Jiang, C. (2024). Dose My Opinion Count? A CNN-LSTM Approach for Sentiment Analysis of Indian General Elections. Journal of Theory and Practice of Engineering Science, 4(05), 40-50.
Liu, T., Cai, Q., Xu, C., Hong, B., Xiong, J., Qiao, Y., & Yang, T. (2024). Image Captioning in News Report Scenario. Academic Journal of Science and Technology, 10(1), 284-289.
Su, J., Jiang, C., Jin, X., Qiao, Y., Xiao, T., Ma, H., ... & Lin, J. (2024). Large language models for forecasting and anomaly detection: A systematic literature review. arXiv preprint arXiv:2402.10350.
Yi, X., & Qiao, Y. (2024). GPU-Based Parallel Computing Methods for Medical Photoacoustic Image Reconstruction. arXiv preprint arXiv:2404.10928.
Zhao, Z., Zhang, N., Xiong, J., Feng, M., Jiang, C., & Wang, X. (2024). Enhancing E-commerce Recommendations: Unveiling Insights from Customer Reviews with BERTFusionDNN. Journal of Theory and Practice of Engineering Science, 4(02), 38-44.
Peng, Q. (2022). Multi-source and Source-Private Cross-Domain Learning for Visual Recognition (Master's thesis, Purdue University).
Tao, Y., Jia, Y., Wang, N., & Wang, H. (2019, July). The fact: Taming latent factor models for explainability with factorization trees. In Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval (pp. 295-304).
Li, W. (2024). The Impact of Apple's Digital Design on Its Success: An Analysis of Interaction and Interface Design. Academic Journal of Sociology and Management, 2(4), 14-19.
Xu, Y., Lin, Y. S., Zhou, X., & Shan, X. (2024). Utilizing emotion recognition technology to enhance user experience in real-time. Computing and Artificial Intelligence, 2(1), 1388-1388.
Li, K., Xirui, P., Song, J., Hong, B., & Wang, J. (2024). The application of augmented reality (ar) in remote work and education. arXiv preprint arXiv:2404.10579.
Zou, Z.-B., Song, L.-P., & Song, Z.-L. (2017). Labeled box-particle PHD filter for multi-target tracking. 2017 3rd IEEE International Conference on Computer and Communications (ICCC), 1725–1730. IEEE.
Peng, Q., Zheng, C., & Chen, C. Source-free Domain Adaptive Human Pose Estimation (Supplementary Material).
Liu, T., Xu, C., Qiao, Y., Jiang, C., & Yu, J. (2024). Particle Filter SLAM for Vehicle Localization. Journal of Industrial Engineering and Applied Science, 2(1), 27-31.
Pinyoanuntapong, E., Ali, A., Jakkala, K., Wang, P., Lee, M., Peng, Q., ... & Sun, Z. (2023, September). Gaitsada: Self-aligned domain adaptation for mmwave gait recognition. In 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS) (pp. 218-226). IEEE.
Qu, P., Zhang, B., Wu, J., & Yan, H. (2024). Comparison of Text Classification Algorithms based on Deep Learning. Journal of Computer Technology and Applied Mathematics, 1(2), 35-42.
Wang, L., Xiao, W., & Ye, S. (2019). Dynamic Multi-label Learning with Multiple New Labels. In Image and Graphics: 10th International Conference, ICIG 2019, Beijing, China, August 23–25, 2019, Proceedings, Part III 10 (pp. 421-431). Springer International Publishing.
Wu, R., Zhang, T., & Xu, F. (2024). Cross-Market Arbitrage Strategies Based on Deep Learning. Academic Journal of Sociology and Management, 2(4), 20-26.
Zou, Z., Careem, M., Dutta, A., & Thawdar, N. (2023). Joint spatio-temporal precoding for practical non-stationary wireless channels. IEEE Transactions on Communications, 71(4), 2396-2409.
Zhibin, Z. O. U., Liping, S., & Xuan, C. (2019). Labeled box-particle CPHD filter for multiple extended targets tracking. Journal of Systems Engineering and Electronics, 30(1), 57–67.
Zhou, Z., Xu, C., Qiao, Y., Xiong, J., & Yu, J. (2024). Enhancing Equipment Health Prediction with Enhanced SMOTE-KNN. Journal of Industrial Engineering and Applied Science, 2(2), 13-20.
Peng, Q., Zheng, C., & Chen, C. (2023). Source-free domain adaptive human pose estimation. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 4826-4836).
Wang, L. (2024). The Impact of Network Load Balancing on Organizational Efficiency and Managerial Decision-Making in Digital Enterprises. Academic Journal of Sociology and Management, 2(4), 41-48.
Wang, L. (2024). Low-Latency, High-Throughput Load Balancing Algorithms. Journal of Computer Technology and Applied Mathematics, 1(2), 1-9.
Feng, M., Wang, X., Zhao, Z., Jiang, C., Xiong, J., & Zhang, N. (2024). Enhanced Heart Attack Prediction Using eXtreme Gradient Boosting. Journal of Theory and Practice of Engineering Science, 4(04), 9-16.
Guo, F., Mo, H., Wu, J., Pan, L., Zhou, H., Zhang, Z., ... & Huang, F. (2024). A Hybrid Stacking Model for Enhanced Short-Term Load Forecasting. Electronics, 13(14), 2719.
Wang, L. (2024). Network Load Balancing Strategies and Their Implications for Business Continuity. Academic Journal of Sociology and Management, 2(4), 8-13.
Jia, J., Wang, N., Liu, Y., & Li, H. (2024). Fast Two-Grid Finite Element Algorithm for a Fractional Klein-Gordon Equation. Contemporary Mathematics, 1164-1180.
Zhao, Y., Wu, J., Qu, P., Zhang, B., & Yan, H. (2024). Assessing User Trust in LLM-based Mental Health Applications: Perceptions of Reliability and Effectiveness. Journal of Computer Technology and Applied Mathematics, 1(2), 19-26.
Wang, L., Fang, W., & Du, Y. (2024). Load Balancing Strategies in Heterogeneous Environments. Journal of Computer Technology and Applied Mathematics, 1(2), 10-18.
Chen, Q., & Wang, L. (2024). Social Response and Management of Cybersecurity Incidents. Academic Journal of Sociology and Management, 2(4), 49-56.
Zhu, M., Zhang, Y., Gong, Y., Xu, C., & Xiang, Y. Enhancing Credit Card Fraud Detection: A Neural Network and SMOTE Integrated Approach. Journal of Theory and Practice of Engineering Science ISSN, 2790, 1513.
Wang, X., Qiao, Y., Xiong, J., Zhao, Z., Zhang, N., Feng, M., & Jiang, C. (2024). Advanced network intrusion detection with tabtransformer. Journal of Theory and Practice of Engineering Science, 4(03), 191-198.
Peng, Q., Ding, Z., Lyu, L., Sun, L., & Chen, C. (2023, August). RAIN: regularization on input and network for black-box domain adaptation. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (pp. 4118-4126).
Zhu, A., Liu, J., Li, K., Dai, S., Hong, B., Zhao, P., & Wei, C. (2024). Exploiting Diffusion Prior for Out-of-Distribution Detection. arXiv preprint arXiv:2406.11105.
Tao, Y. (2023, October). SQBA: sequential query-based blackbox attack. In Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023) (Vol. 12803, pp. 721-729). SPIE.
Xu, C., Yu, J., Chen, W., & Xiong, J. (2024, January). Deep learning in photovoltaic power generation forecasting: Cnn-lstm hybrid neural network exploration and research. In The 3rd International Scientific and Practical Conference (Vol. 363, p. 295).
Peng, Q., Ding, Z., Lyu, L., Sun, L., & Chen, C. (2022). Toward better target representation for source-free and black-box domain adaptation. arXiv preprint arXiv:2208.10531, 3.
Tao, Y. (2023, August). Meta Learning Enabled Adversarial Defense. In 2023 IEEE International Conference on Sensors, Electronics and Computer Engineering (ICSECE) (pp. 1326-1330). IEEE.
Guo, F. (2023, July). A study of smart grid program optimization based on k-mean algorithm. In 2023 3rd International Conference on Electrical Engineering and Mechatronics Technology (ICEEMT) (pp. 711-714). IEEE.
Zou, Z., Careem, M., Dutta, A., & Thawdar, N. (2022, May). Unified characterization and precoding for non-stationary channels. In ICC 2022-IEEE International Conference on Communications (pp. 5140-5146). IEEE.
Zou, Z., Careem, M., Dutta, A., & Thawdar, N. (2022). Unified characterization and precoding for non-stationary channels. ICC 2022-IEEE International Conference on Communications, 5140–5146. IEEE.
Guo, F., Wu, J. Z., & Pan, L. (2023, July). An Empirical Study of AI Model’s Performance for Electricity Load Forecasting with Extreme Weather Conditions. In International Conference on Science of Cyber Security (pp. 193-204). Cham: Springer Nature Switzerland.
Song, C. (2024). Optimizing Management Strategies for Enhanced Performance and Energy Efficiency in Modern Computing Systems. Academic Journal of Sociology and Management, 2(4), 57-64.
Song, C. (2024). Optimizing Management Strategies for Enhanced Performance and Energy Efficiency in Modern Computing Systems. Academic Journal of Sociology and Management, 2(4), 57-64.
Xu, C., Qiao, Y., Zhou, Z., Ni, F., & Xiong, J. (2024). Accelerating Semi-Asynchronous Federated Learning. arXiv preprint arXiv:2402.10991.
Xu, C., Qiao, Y., Zhou, Z., Ni, F., & Xiong, J. (2024). Enhancing Convergence in Federated Learning: A Contribution-Aware Asynchronous Approach. Computer Life, 12(1), 1-4.
Peng, Q., Zheng, C., & Chen, C. (2024). A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2240-2249).
Li, K., Zhao, P., Dai, S., Zhu, A., Hong, B., Liu, J., ... & Zhang, Y. (2024). Exploring the Impact of Quantum Computing on Machine Learning Performance.
Downloads
Published
How to Cite
Issue
Section
ARK
License
Copyright (c) 2024 The author retains copyright and grants the journal the right of first publication.
This work is licensed under a Creative Commons Attribution 4.0 International License.
