Analyzing Failures and Challenges in Oncology: Integration of Artificial Intelligence in Healthcare

Year : 2024 | Volume :13 | Issue : 01 | Page : 42-50
By

Sudha

Jayashri K

  1. Assistant Professor Shri Shankarlal Sundarbai Shasun Jain College for Women Tamil Nadu India
  2. Student Shri Shankarlal Sundarbai Shasun Jain College for Women Tamil Nadu India

Abstract

The present study focused on investigating the challenges and failures that had been embarked during the deployment of artificial intelligence technologies within the field of oncology in healthcare. Through precise research and statistical analysis, we aimed to elucidate the specific circumstances surrounding each failure, providing insights into the root causes, consequences, and subsequent developments. The present study was aimed to offer a detailed understanding of the challenges faced through artificial intelligence in healthcare. The primary objectives included identifying common patterns and root causes of the failed tech, assessing the impact on patient care, and exploring potential solutions to mitigate risks and successful integration of artificial intelligence in oncology. The outcomes derived from our study were focused at fostering a more knowledgeable and resilient incorporation of artificial intelligence, emphasizing advancements that prioritize ethical concerns. By doing so, we aspire to catalyze improvements in healthcare outcomes through the conscientious and thoughtful integration of artificial intelligence technologies.

Keywords: artificial intelligence, oncology, challenges, robust, ethical, deployment

[This article belongs to Research & Reviews: Journal of Oncology and Hematology(rrjooh)]

How to cite this article: Sudha, Jayashri K. Analyzing Failures and Challenges in Oncology: Integration of Artificial Intelligence in Healthcare. Research & Reviews: Journal of Oncology and Hematology. 2024; 13(01):42-50.
How to cite this URL: Sudha, Jayashri K. Analyzing Failures and Challenges in Oncology: Integration of Artificial Intelligence in Healthcare. Research & Reviews: Journal of Oncology and Hematology. 2024; 13(01):42-50. Available from: https://journals.stmjournals.com/rrjooh/article=2024/view=143837




References

  1. Takyar A. AI Use Cases & Applications Across Major industries. USA: LeewayHertz – AI Development Company; Available from: https://www.leewayhertz.com/ai-use-cases-and-applications/.
  2. Luchini C, Pea A, Scarpa Artificial intelligence in oncology: Current applications and future perspectives. British Journal of Cancer. 2022; 126: 4–9p.
  3. Shaheen Applications of Artificial Intelligence (AI) in healthcare: A review. Science Open Preprints; 2021. DOI: 10.14293/S2199-1006.1.SOR-.PPVRY8K.v1
  4. Ko CC, Yeh LR, Kuo YT, Chen JH. Imaging biomarkers for evaluating tumor response: RECIST and beyond. Biomarker Research. 2021; 9(1): 52p.
  5. Secinaro S,Calandra D, Secinaro A, Muthurangu V, Biancone P. The role of artificial intelligence in healthcare: a structured literature review. BMC Medical Informatics and Decision Making. 2021; 21: 1–23p.
  6. Alshuhri M, Al-Musawi SG, Al-Alwany AA, Uinarni H, Rasulova I, et al. Artificial intelligence in cancer diagnosis: Opportunities and challenges. Pathology-Research and Practice. 2023; 253:
  7. Wang L, Zhang Y, Wang D, Tong X, Liu T, et al. Artificial intelligence for COVID-19: a systematic review. Frontiers in M 2021; 8: 1457.
  8. Drysdale E, Dolatabadi E, Chivers C, Liu V, Saria S, et al. Implementing AI in healthcare. Proceedings of the Vector-SickKids Health AI Deployment Symposium; 2019 Oct 30; Toronto, Canada.
  9. Shah R, Chircu IOT And AIin Healthcare: A Systematic Literature Review. Issues in Information Systems. 2018; 19(3): 33–41p.
  10. Senbekov M, Saliev T, Bukeyeva Z, Almarai A, Zhanaliyeva M, et al. The Recent Progress and Applications of Digital Technologies in Healthcare: A Review. International Journal of Telemedicine and Applications. 2020; 2020: 8830200.
  11. Banner N, Hall A, Ordish J, Raza Artificial Intelligence in Healthcare and research. London: Nuffield Council on Bioethics; 2018. Available from: https://www.nuffieldbioethics.org/wp-content/uploads/Artificial-Intelligence-AI-in-healthcare-and-research.pdf
  12. Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019; 6(2): 94–98p. doi: 10.7861/futurehosp.6-2-94. PMID: 31363513; PMCID: PMC6616181.
  13. Westenberger J, Schuler K, Schlegel D. Failure of AI projects: understanding the critical factors. Procedia Computer Science. 2022; 196: 69–76p. Available from: https://www.sciencedirect.com/science/article/pii/S1877050921022134
  14. Lee D, Yoon SN. Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges. International Journal of Environmental Research and Public H 2021; 18(1): 271p.
  15. Holm S, Stanton C, Bartlett B. A new argument for no-fault compensation in health care: the introduction of artificial intelligence systems. Health Care Analysis. 2021; 29: 171–188p.
  16. González-Gonzalo C, Thee EF, Klaver CCW, Lee AY, Schlingemann RO, et al. Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice. Prog Retin Eye Res. 2022; 90: Available from: https://researchinformation.amsterdamumc.org/en/publications/trustworthy-ai-closing-the-gap-between-development-and-integratio
  17. González-Gonzalo C, Thee EF, Klaver CCW, Lee AY, Schlingemann RO, et al. Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice. Progress in Retinal and Eye Research. 2022; 90:101034–4.
  18. Nayak S, Kumar Das R. Application of Artificial Intelligence (AI) in Prosthetic and Orthotic Rehabilitation. Service Robotics. IntechOpen; Available from: http://dx.doi.org/10.5772/intechopen.93903
  19. Zhang M, Li M, Guo L, Liu J. A low-cost AI-empowered stethoscope and a lightweight model for detecting cardiac and respiratory diseases from lung and heart auscultation sounds. Sensors. 2023; 23(5):
  20. Soori M, Arezoo B, Dastres R. Artificial Intelligence, Machine Learning and Deep Learning in Advanced Robotics, A Review. Cognitive Robotics. 2023; 3: 54–70p.

Regular Issue Subscription Review Article
Volume 13
Issue 01
Received January 20, 2024
Accepted March 1, 2024
Published April 20, 2024