Authors :
R. Umme Hafsa; Jennifer Mary S.
Volume/Issue :
Volume 11 - 2026, Issue 5 - May
Google Scholar :
https://tinyurl.com/mtkzntdd
Scribd :
https://tinyurl.com/mpncndmb
DOI :
https://doi.org/10.38124/ijisrt/26May920
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The growing use of Online medical service systems are becoming more widely used the need for accurate and safe
child healthcare guidance. CARESURE AI is an intelligent mobile-based advisory system designed to help parents
understand common pediatric symptoms and access verified medicine information without replacing professional medical
care. The system uses a cloud-enabled architecture with AI-driven rule-based analysis to evaluate child age, symptoms, and
severity. By processing user inputs, the application provides precautionary advice, safety alerts, and medicine guidance
aligned with pediatric standards. Ethical AI principles are followed by avoiding diagnosis and recommending medical
consultation for critical cases. Experimental results using simulated health scenarios show that CARESURE AI effectively
improves health awareness and supports safe decision-making in child healthcare.
Keywords :
Child Health Advisory System, AI-Based Healthcare, Pediatric Symptom Analysis, Verified Medicine Guidance, Mobile Health Application, Ethical AI, Health Decision Support System, Preventive Healthcare.
References :
- Shortliffe, E. H., & Cimino, J. J. (2014). Biomedical informatics: Computer applications in health care and biomedicine. Springer. → Provides foundational concepts of AI-based decision support in healthcare systems.
- Topol, E. J. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. → Discusses the contribution of artificial intelligence in improving healthcare decision-making and patient safety.
- Jiang, F., Jiang, Y., Zhi, H., et al. (2017). Artificial intelligence in healthcare: Past, present, and future. Stroke and Vascular Neurology, 2(4), 230–243. → Explains the evolution of AI techniques used in healthcare applications.
- Shah, S. G. S., & Robinson, I. (2007). Benefits of and barriers to involving users in medical device technology development. Technology and Health Care, 15(4), 287–301. → Highlights the importance of usability and trust in health-related systems.
- Kumar, S., Nilsen, W., Pavel, M., & Srivastava, M. (2013). Mobile health: Revolutionizing healthcare through transdisciplinary research. Computer, 46(1), 28–35. → Provides insights into mobile health (mHealth) applications and real-time health monitoring.
- World Health Organization (WHO). (2019). WHO guideline: Recommendations on digital interventions for health system strengthening. → Establishes ethical and safety principles for digital health advisory systems.
- Razzak, M. I., Imran, M., & Xu, G. (2019). Big data analytics for preventive medicine. Neural Computing and Applications, 32, 4417–4451. → Discusses how data-driven systems can support preventive healthcare.
- Miller, D. D., & Brown, E. W. (2018). Artificial intelligence in medical practice: The question to the answer? American Journal of Medicine, 131(2), 129–133. → Emphasizes ethical AI usage and limitations of automated medical advice.
- Islam, S. M. R., Kwak, D., Kabir, M. H., Hossain, M., & Kwak, K. S. (2015). The Internet of Things for health care: A comprehensive survey. IEEE Access, 3, 678–708. → Supports future scope involving smart health monitoring and wearable integration.
- Beauchamp, T. L., & Childress, J. F. (2013). Principles of biomedical ethics. Oxford University Press. → Provides ethical foundations relevant to child health advisory systems.
The growing use of Online medical service systems are becoming more widely used the need for accurate and safe
child healthcare guidance. CARESURE AI is an intelligent mobile-based advisory system designed to help parents
understand common pediatric symptoms and access verified medicine information without replacing professional medical
care. The system uses a cloud-enabled architecture with AI-driven rule-based analysis to evaluate child age, symptoms, and
severity. By processing user inputs, the application provides precautionary advice, safety alerts, and medicine guidance
aligned with pediatric standards. Ethical AI principles are followed by avoiding diagnosis and recommending medical
consultation for critical cases. Experimental results using simulated health scenarios show that CARESURE AI effectively
improves health awareness and supports safe decision-making in child healthcare.
Keywords :
Child Health Advisory System, AI-Based Healthcare, Pediatric Symptom Analysis, Verified Medicine Guidance, Mobile Health Application, Ethical AI, Health Decision Support System, Preventive Healthcare.