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

Artificial Intelligence in Diagnostic Healthcare

Abstract

Artificial Intelligence, or AI, is changing the way doctors diagnose diseases by mixing computer power with medical knowledge. It helps doctors make quicker and more accurate decisions based on data, allowing them to catch illnesses sooner and with more precision. This paper looks at how AI is used to improve diagnosis through methods like machine learning, deep learning, and understanding human language. It covers real examples of AI being used in medical scans, studying tissue samples, and predicting health issues. The paper also talks about the advantages, challenges, and important questions about using AI in medicine. It shows how AI can help reduce mistakes, work faster, and support tailored treatments for patients. The study also looks at problems like keeping patient information safe, making AI decisions clear, and following rules. It finishes by saying that using AI in a smart and responsible way can make healthcare better, fairer, and more available for everyone.

Country : India

1 Prof.S.B.Bele2 Karunesh Deshmukh3 Puja Hood4 Rutika Dhande5 Sajal Kale

  1. Department of MCA, Vidya Bharti Mahavidyalaya, Amravati, Maharashtra, India
  2. Department of MCA, Vidya Bharti Mahavidyalaya, Amravati, Maharashtra, India
  3. Department of MCA, Vidya Bharti Mahavidyalaya, Amravati, Maharashtra, India
  4. Department of MCA, Vidya Bharti Mahavidyalaya, Amravati, Maharashtra, India
  5. Department of MCA, Vidya Bharti Mahavidyalaya, Amravati, Maharashtra, India

IRJIET, Volume 9, Issue 10, October 2025 pp. 164-168

doi.org/10.47001/IRJIET/2025.910022

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References

  1. J. Smith, M. Patel, and L. Johnson, “AI in Medical Imaging: A Comprehensive Review,” Journal of Healthcare Informatics, vol. 8, no. 2, pp. 45–52, 2023.
  2. P. Kumar and A. Sharma, “Machine Learning Applications in Pathology,” IEEE Transactions on Medical Systems, vol. 12, no. 4, pp. 67–73, 2022.
  3. L. Brown, “Ethical Challenges in AI Healthcare,” International Journal of AI Ethics, vol. 3, no. 1, pp. 15–26, 2024.
  4. R. Gupta and D. Mehta, “Deep Learning for Disease Prediction and Diagnostics,” Elsevier Medical Data Science, vol. 10, no. 3, pp. 99–108, 2023.
  5. S. Zhang, C. Liu, and T. Wong, “Future of AI in Personalized Medicine,” Nature Biomedical Engineering, vol. 6, no. 5, pp. 205–214, 2024.
  6. H. Anderson and J. Torres, “AI-Assisted Radiology: From Image Recognition to Clinical Insight,” IEEE Access, vol. 11, pp. 15220–15235, 2023.
  7. M. Chen et al., “Artificial Intelligence in Cardiology: Diagnosis, Risk Stratification, and Prognosis,” European Heart Journal – Digital Health, vol. 5, no. 2, pp. 200–213, 2024.
  8. K. Singh and R. Bhatia, “Deep Neural Networks for Cancer Detection in Histopathology Images,” Frontiers in Oncology, vol. 13, article 11245, 2023.
  9. J. Taylor, “AI in Diagnostic Radiology: Opportunities and Limitations,” Radiographics, vol. 43, no. 4, pp. 965–982, 2023.
  10. A.Fernandez and S. Kumar, “Predictive Analytics in Healthcare Using AI and Big Data,” Health Informatics Journal, vol. 29, no. 1, pp. 150–169, 2024.
  11. N. Ramesh and V. Thomas, “AI-Enabled Clinical Decision Support Systems,” IEEE Engineering in Medicine and Biology Magazine, vol. 41, no. 6, pp. 45–55, 2023.
  12. J. Wang, “Machine Learning in Medical Imaging: Current Status and Future Directions,” Annual Review of Biomedical Engineering, vol. 25, pp. 55–80, 2023.
  13. B. Patel and D. Kapoor, “AI in Healthcare Data Management: Challenges and Solutions,” Journal of Digital Health Systems, vol. 7, no. 3, pp. 199–210, 2023.
  14. F. Rossi et al., “Natural Language Processing for Clinical Data Mining,” Journal of Biomedical Informatics, vol. 142, 104386, 2023.
  15. T. Nguyen and P. Lee, “Blockchain and AI Integration for Secure Medical Data Sharing,” IEEE Internet of Things Journal, vol. 11, no. 1, pp. 340–352, 2024.
  16. M. Al-Hussein and E. Rahman, “AI-Driven Early Detection of Diabetic Retinopathy Using Retinal Images,” Computers in Biology and Medicine, vol. 159, 106017, 2023.
  17. G. Park and H. Lim, “Wearable AI Devices for Continuous Health Monitoring,” Sensors, vol. 24, no. 8, pp. 3520–3536, 2024.
  18. Y. Zhao and L. Chen, “Ethical and Legal Challenges in Artificial Intelligence– Driven Healthcare,” Journal of Medical Ethics and Law, vol. 18, no. 2, pp. 77–89, 2024.
  19. D. Verma, “IoT-Enabled AI Diagnostics in Rural Healthcare,” IEEE Transactions on Emerging Topics in Computing, vol. 12, no. 3, pp. 445–456, 2024.
  20. E. Johnson, “The Future Landscape of AI in Diagnostic Medicine: Challenges and Possibilities,” Nature Digital Medicine, vol. 7, no. 9, pp. 110–122, 2025.

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