STM Journals Peer-reviewed research from Consortium e-Learning Network

Research and Reviews : A Journal of Medical Science and Technology Original Research

DR. REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care

  1. Sohini Tandon Department of Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University)
  2. Mohammad Ehtesham Department of Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University)
  3. Mohd. Rizwan Khan Department of Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University)
  4. Mohammad Ehsan Department of Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University)
  5. Md. Yasir Department of Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University)
  6. Sunil Department of Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University)
  7. Sayeed Mohd. Ameen Department of Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Technology, Jamia Millia Islamia (A Central University)

Abstract

Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete overview of patient information, Dr. Revive enables doctors to prioritise urgent cases, improving consultation efficiency. Beyond medical recommendations, Dr. Revive includes features such as health tracking, diagnostic test suggestions, prescription management, and continuous feedback mechanisms, ensuring precision and adaptability in patient care. By streamlining communication between patients and healthcare providers, the platform minimises miscommunication and fosters better coordination among hospitals, diagnostic labs, and blood banks. This integrated system enhances resource allocation, optimising medical workflows and boosting overall efficiency. By reducing administrative burdens and improving accessibility, Dr. Revive significantly shortens patient wait times and enhances healthcare delivery, particularly in regions with limited medical infrastructure. The paper explores the system’s design, functionality, and impact, highlighting its role in addressing critical healthcare challenges and advancing toward a more efficient, patient-focused, and technology-driven healthcare ecosystem.

Keywords

References (19)

  1. Heydari M, Foroughi Z, Ghasab AA, Koohpaei A, Abardeh MH, Nouhi M. Medical Education Quality in the COVID-19 Era: A Policy Brief on Lesson Learned and Recommendations. Evidence Based Health Policy, Management and Economics. 2024. doi:10.18502/jebhpme.v8i2.17180
  2. J A, Isravel DP, Sagayam KM, Bhushan B, Sei Y, Eunice J. Blockchain for healthcare systems: Architecture, security challenges, trends and future directions. Journal of Network and Computer Applications. 2023;215:103633. doi:10.1016/j.jnca.2023.103633
  3. Suhel S, Parwez S, Siddique S, Fatma N, Shadab M, Sunil. An online mobile-based doctor appointment booking application to enhance the acceptability of healthcare systems. In: Proc Natl Conf Res Adv Innov Comput Commun Inf Technol (RAICCIT 2023); 2023; JIS Univ, Agarpara, Kolkata, India.
  4. Avinash B, Joseph G. Reimagining healthcare supply chains: a systematic review on digital transformation with specific focus on efficiency, transparency and responsiveness. Journal of Health Organization and Management. 2024;38(8):1255-1279. doi:10.1108/jhom-03-2024-0076
  5. Mnsour E, Trust E. Applications of artificial intelligence towards sustainable healthcare systems: The next generation in patient care—AI-powered hospital beds. 2024;10:52-6.
  6. Esther D, Blake H. AI-powered decision support systems in medicine: A comprehensive analysis. 2024.
  7. Oladele O. AI-powered medical imaging: A comprehensive review of applications, benefits, and challenges. 2024.
  8. Fatma H, Ahmad M, Sunil. Analyzing the role of artificial intelligence in modern healthcare systems. In: Proc Natl Conf Res Adv Innov Comput Commun Inf Technol (RAICCIT 2023); 2023; JIS Univ, Agarpara, Kolkata, India.
  9. Akinyele D. Revolutionizing patient care and accessible healthcare delivery through AI-powered virtual assistants. 2024.
  10. Ghorashi N, Ismail A, Ghosh P, Sidawy A, Javan R. AI-Powered Chatbots in Medical Education: Potential Applications and Implications. Cureus. 2023. doi:10.7759/cureus.43271
  11. Sunil, Ahmad M, Fatma H. Artificial intelligence in healthcare: Issues and challenges. In: Proc Int Conf Adv Comput (ICAC-2024); 2024; SRMS College of Eng & Tech, Bareilly, Uttar Pradesh, India.
  12. Kumar H, Parveen R, Adnan, Sunil. Trends and future research directions in intelligent healthcare recommendation systems: A review. In: Proc Natl Conf Res Adv Innov Comput Commun Inf Technol (RAICCIT 2023); 2023; JIS Univ, Agarpara, Kolkata, India.
  13. Alharbi ORS, Alhrbi BSM, Al-Rashidi AMH, Alzabni ASM, Al Harbi AFA, Alharbi ASM, et al. Critical Analysis of Foundational Challenges in Modern Healthcare Systems. Journal of Ecohumanism. 2024;3(8). doi:10.62754/joe.v3i8.5084
  14. Advancing Accuracy with Ai-Driven Approaches for Automated Detection and Segmentation of Brain Tumours. Cuestiones de fisioterapia. 2025;54(3). doi:10.48047/cu/54/03/2192-2199
  15. Gorrepati LP. Integrating AI with Electronic Health Records (EHRs) to Enhance Patient Care. International Journal of Health Sciences. 2024;7(8):38-50. doi:10.47941/ijhs.2368
  16. Amponin AM, Britiller MC. Electronic Health Records (EHRs): Effectiveness to Health Care Outcomes and Challenges of Health Practitioners in Saudi Arabia. Saudi Journal of Nursing and Health Care. 2023;6(04):123-135. doi:10.36348/sjnhc.2023.v06i04.002
  17. Sunil, Fatma H, Ahmad M. Intelligent healthcare recommender system for advanced healthcare services. In: Proc 4th Int Conf ICT Digit Smart Sustain Dev (ICIDSSD-2024); 2024; Jamia Hamdard, New Delhi, India. ISBN:978-93-340-0613-1.
  18. Sunil, Fatma H, Ahmad M. Enhancing accuracy with AI-powered methods for automated detection and segmentation of brain tumours. Int J Emerg Technol Innov Res. 2025;12(1):g736-g742. ISSN:2349-5162.
  19. Fayaq M. Build Hospital Management System using PHP framework. Iraqi Journal of Intelligent Computing and Informatics (IJICI). 2023;2(2):101-112. doi:10.52940/ijici.v2i2.35
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