International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

A Mechanism to Ensure the Immunization Rate of Newborns with Novel Techniques via Remote Consultation

Abstract

This study addresses the deficiency in Sri Lanka's infant health system by proposing a comprehensive approach. This approach consists of a decentralized patient information system for secure access to patient data, a chatbot for parental guidance, an image-based skin disease identifier, a growth predictor, and a module for early sickness detection. These components collectively enhance infant healthcare by improving data accessibility, enabling remote guidance, predicting growth levels, and identifying unusual behaviors. This integrated solution aims to mitigate existing data and accessibility challenges, fostering timely and informed actions for better baby healthcare in Sri Lanka.

Country : Sri Lanka

1 Udara Wijesinghe2 Disni Jayawickrama3 Ramona Vanhoff4 Anodya Poojani Fernando5 Dr. Nuwan Kodagoda6 Mr. Thusithanjana Thilakarthna

  1. Computer Science and Software Engineering Department, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  2. Computer Science and Software Engineering Department, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  3. Computer Science and Software Engineering Department, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  4. Computer Science and Software Engineering Department, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  5. Computer Science and Software Engineering Department, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  6. Computer Science and Software Engineering Department, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka

IRJIET, Volume 7, Issue 10, October 2023 pp. 258-265

doi.org/10.47001/IRJIET/2023.710033

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References

  1. Syed Agha Hassnain Mohsan, A. R.-K. (2022). Decentralized Patient-Centric Report and Medical Image. Environ. Res. Public Health, 18.
  2. Vest, J.R.; Gamn, L.D. Health Information Exchange: Persistent Challenges and New Strategies. J.Am. Med. Inform. Assoc. 2010,17, 288–294.
  3. Zhang, M.; Chen, Y.; Susilo, W. PPO-CPQ: A Privacy- Preserving Optimization of Clinical Pathway Query for E- Healthcare Systems. IEEE Internet Things J. 2020, 7, 10660– 10672.
  4. Duan, C.; Deng, H.; Xiao, S.; Xie, J.; Li, H.; Zhao, X.; Han, D.; Sun, X.; Lou, X.; Ye, C.; et al. Accelerate gas diffusion- weighted MRI for lung morphometry with deep learning. Eur. Radiol. 2022, 32, 702–713.
  5. C C Darshan Thimmaiah, D. S. (2019). Decentralized Electronic Medical Records. International Journal of Research and Analytical Reviews, 5.
  6. B. Narendra Kumar Rao, B. B. (2019). Block chain Based Implementation of Electronic. International Journal of Innovative Technology and Exploring Engineering, 16.
  7. B. Setiaji and F. W. Wibowo, "Chatbot Using A Knowledge in Database," in 7th International Conference on Intelligent Systems, Modelling, and Simulation, 2016.
  8. S. J. du Preez, M. Lall, and S. Sinha, "An Intelligent Web- based voice chatbot," IEEE, 2009.
  9. K. Mohanapriya, R. Suganya, and R. Hemalatha, "Medical Assistance Chatbot," in 2019 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 2019, pp. 1-4, doi: 10.1109/CCCI.2019.8816904.
  10. S. Trivedi, A. Lalani, and S. K. Patel, "COVID-19 screening chatbot: A design and evaluation," in 2020 IEEE 17th India Council International Conference (INDICON), Bangalore, India, 2020, pp. 1- 5, doi: 10.1109/INDICON50694.2020.9341975.
  11. S. Baker et al., "A randomized controlled trial evaluating a low- intensity interactive online parenting intervention, Triple P Online Brief, with parents of children with early onset conduct problems," IEEE, 2017.
  12. Chi-Shun Yu, Mei-Hua Hsu, Yung-Chung Wang, and Yi-Jie You,” Designing a Chatbot for Helping Parenting Practice”, 2023.
  13. B. Kriström and K. A. Wikland, "Growth prediction models, concept and use," Hormone Research, vol. 57, Suppl. 2, pp. 66-70, 2002. DOI: 10.1159/000058104.
  14. W. F. Dearborn and J. W. M. Rothney, "Predicting the child's development," Sci-Art Publishers, 1941.
  15. M. K. C. Nair and V. Mehta, "Life cycle approach to child development," Indian Pediatrics, vol. 44, no. 7, pp. 529-534, 2007.
  16. C. Barkmann, N. Helle, and C. Bindt, "Is very low infant birth weight a predictor for a five-year course of depression in parents? A latent growth curve model," Journal of Affective Disorders, vol. 213, pp. 79-85, 2017. DOI: 10.1016/j.jad.2017.02.024.
  17. Sultana, S., Mollah, M. F., Hossain, M. S., & Ahmed, S. H. (2021). "Deep Learning for Abnormal Behavior Detection in Videos: A Survey." arXiv preprint arXiv:2101.05845. Retrieved from https://arxiv.org/abs/2101.05845.
  18. Zia, M. A., Arshad, N., & Tariq, S. A. (2018). "Abnormal Behavior Detection in Infants Using Computer Vision Techniques."
  19. Nguyen, W. W., Tran, D., & AlRegib, G. (2020). "Real-Time Video-Based Abnormal Infant Behavior Detection using Deep Learning."
  20. Zhang, L., Zhang, Z., & Cheng, L. (2019). "Abnormal Infant Behavior Recognition using 3D Convolutional Neural Networks."
  21. Jung Hyuk Lee, Geon Woo Lee Ma, G., Guiyong Bong, Hee Jeong Yoo & Hong Kook Kin (2020). "Deep-Learning-Based Detection of Infants with Autism Spectrum Disorder Using Auto- Encoder Feature Representation." [MDPI], [20(23)] (6762), Retrieved from [https://doi.org/10.3390/s20236762.

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