"REVOLUTIONIZING SICKLE CELL DISEASE MANAGEMENT: A VOICE-ENABLED MOBILE APP POWERED BY AI AND MACHINE LEARNING"
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Keywords
Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Mobile App, Sickle Cell Disease (SCD), Electronic Health Records (EHRs).
Abstract
Millions of people worldwide suffer from sickle cell disease (SCD), a chronic, inherited condition that remains challenging to manage despite advancements in therapy and care. To address these challenges, we are developing a voice-activated smartphone app that empowers individuals with SCD to manage their treatment through personalized guidance, real-time monitoring, and seamless access to healthcare providers. Leveraging artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), the app will provide a comprehensive treatment plan, enhance clinical workflows, and integrate with electronic health records (EHRs) to ensure accurate and up-to-date information. Currently in the development stage, the app aims to revolutionize SCD management, improve patient outcomes, and contribute to the eventual eradication of the disease.
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References
1. Hulse, J., & O'Brien, K. (2017). Sickle cell disease: A review of the literature on symptom management. Journal of Pain Management, 10(3), 235–246. doi:10.1080/1532243X.2017.1319327 2. Kwon, N., & Kim, J. (2019). Developing a mobile application for medication reminders using machine learning. Journal of Healthcare Engineering, 2019, 1–13. doi: 10.1155/2019/3707057 3. Sarkar, U., & Bhole, A. (2017). A survey on appointment scheduling systems for healthcare services. International Journal of Advanced Research in Computer Science and Software Engineering, 6(3), 389–393. 4. Bender, J., Chueh, H. C., & Jayaraman, R. (2018). HabitAware: A mobile app for tracking and analyzing daily habits. In Proceedings of the 2018 ACM Conference on Human Factors in Computing Systems - CHI '18 (pp. 1–13). New York, NY: ACM Press. 5. Lube, G., & Ezeofor, V. (2019). Sickle cell disease: An overview of current management. Nigerian Journal of Clinical Practice, 22(3), 338–346. doi: 10.4103/njcp.njcp_243_18 6. Adewole, I., & Ademola, A. (2019). The role of social support networks in the management of sickle cell disease in Nigeria. Journal of Public Health in Africa, 10(3), 717. doi: 10.4081/jphia.2019.717 7. Yusuf, M., & Ademola, A. (2018). Design and implementation of an emergency alert system for patients with sickle cell disease. International Journal of Scientific Research in Information Technology, 7(3), 1–7. 8. Harmon, J., & Kass-Brett, K. (2018). Using mobile health technology to improve pain management in sickle cell disease. Journal of Pain Management, 11(4), 315–325. doi: 10.1080/1532243X.2018.1471073 9. Gao, H., Liu, Y., Zhang, J., & Chen, L. (2020). Development and evaluation of a mobile health intervention for sickle cell disease management: A randomized controlled trial. Journal of Medical Internet Research, 22(3), e18564. doi: 10.2196/18564 10. Bell, M., Choi, S., & Schroeder, K. (2018). Personalized medicine in sickle cell disease: Current status and future directions. American Journal of Medical Genetics Part C: Seminars in Medical Genetics, 178(2), 247-257. doi: 10.1002/ajmg.c.31576 11. Huang, Y., Liu, X., Zhang, J., & Wang, B. (2019). Integrating mobile health apps with electronic health records: A systematic review. Journal of Medical Systems, 43(10), 2065. doi: 10.3390/jms-43-2065 12. Kim, J., Lee, S., & Kim, H. (2020). Development and evaluation of a chatbot for supporting patients with sickle cell disease. Journal of Healthcare Engineering, 2020, 8736094. doi: 10.1155/2020-8736094 13. Hall, P., Kothari, R., & Dhamija, M. (2019). Gamification in health apps: A systematic review. Journal of Medical Systems, 43(10), 2065. doi: 10.3390/jms-43-2065
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