Recent Research Reviews Journal
IRO Journals
Volume 2 — Issue 1 — June 2023

A Study on Scope of Artificial Intelligence in Diagnostic Medicine

https://doi.org/10.36548/rrrj.2023.1.04
S. P. Santhoshkumar
Department of Information Technology, Rathinam technical Campus, Anna University, Coimbatore, India
H. Lilly Beaulah
Department of CSE, Mahendra College of Engineering, Anna University, Salem
K. Susithra
Department of Information Technology, Rathinam technical Campus, Anna University, Coimbatore, India
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How to Cite

Santhoshkumar, S. P., H. Lilly Beaulah, and K. Susithra. 2023. “A Study on Scope of Artificial Intelligence in Diagnostic Medicine”. Recent Research Reviews Journal 2 (1): 39-53. https://doi.org/10.36548/rrrj.2023.1.04.
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Keywords

— AI applications in healthcare
— Artificial Intelligence in healthcare market
— Artificial Intelligence in medical science
— Use of Artificial intelligence
Published: 30-05-2023

Abstract

Artificial Intelligence techniques are used to improve patient care and health systems. The use of machine learning and deep learning in healthcare is indeed prevalent, and it's fascinating to see how different medical data sources can be combined to diagnose diseases accurately. The variety of diseases that can be diagnosed using Artificial Intelligence (AI) techniques is impressive, and it’s interesting to note that different medical imaging datasets are used for feature extraction and classification to make predictions. This highlights the potential of AI in healthcare to assist healthcare providers in identifying diseases and providing appropriate treatments. It is also encouraging to see that AI can enhance the patient experience in hospitals and speed up rehabilitation at home. This can help to improve patient outcomes and reduce healthcare costs. Overall, it's evident that AI has the potential to revolutionize the healthcare industry and improve patient care. As the technology continues to evolve, it will be interesting to see how it is further applied in healthcare and the impact it has on patient outcomes. In this study, the scope of AI in diagnostic medicine has been analysed and summarized.

References

  1. Data Flair, "Importance of AI in Healthcare Sector", https://data-flair.training/blogs/ai-in-healthcare-sector/, 2022.
  2. Yiming Zhang, Ying Weng, Jonathan Lund, "Applications of Explainable Artificial Intelligence in Diagnosis and Surgery", Diagnostics, https://doi.org/10.3390/diagnostics12020237, January 2022.
  3. Humesh Verma , Abhishek Verma , Ankit Mishra, 2022, Theoretical Review on Artificial Intelligence used in the Medical Sector, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 11, Issue 12 (December 2022).
  4. Yogesh Kumar, Apeksha Koul, Ruchi Singla, Muhammad Fazal Ijaz, "Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda", Journal of Ambient Intelligence and Humanized Computing. 13th January 2022, pp. 1–28.
  5. Markus Schmitt, Artificial Intelligence in Medicine - AI for Diagnostics, Drug Development, Treatment Personalisation and Gene Editing, datarevenue, https://www.datarevenue.com/en-blog/artificial-intelligence-in-medicine, 2022.
  6. Zebene A, Årsand E, Walderhaug S, Albers D, Mamykina L, Botsis T, Hartvigsen G (2019) Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes. Artif Intell Med 98:109–134. https://doi.org/10.1016/j.artmed.2019.07.007.
  7. Musleh M, Alajrami E, Khalil A, Nasser B, Barhoom A, Naser S (2019) Predicting liver patients using artificial neural network. J Acad Inf Syst Res 3:1–11.
  8. Dabowsa N, Amaitik N, Maatuk A, Shadi A (2017) A hybrid intelligent system for skin disease diagnosis. In: Conference on engineering and technology, pp 1–6. https://doi.org/10.1109/ICEngTechnol.2017.8308157.
  9. Vasal S, Jain S, Verma A (2020) COVID-AI: an artificial intelligence system to diagnose COVID 19 disease. J Eng Res Technol 9:1–6
  10. Kaur H, Kumari V (2018) Predictive modelling and analytics for diabetes using a machine learning approach. Appl Comput Inform. https://doi.org/10.1016/j.aci.2018.12.004.
  11. Gouda W, Yasin R (2020) COVID-19 disease: CT pneumonia analysis prototype by using artificial intelligence, predicting the disease severity. J Radiol Nucl Med 51:196. https://doi.org/10.1186/s43055-020-00309-9.
  12. Abedi V, Khan A, Chaudhary D, Misra D, Avula V, Mathrawala D, Kraus C, Marshall KA, Chaudhary N, Li X, Schirmer CM, Scalzo F, Li J, Zand R (2020) Using artificial intelligence for improving stroke diagnosis in emergency departments: a practical framework. Ther Adv Neurol Disord. https://doi.org/10.1177/1756286420938962.
  13. Simone Edelmann, "How artificial intelligence in diagnostics is transforming healthcare", HealthcareTransformers - Actionable insights for executives, https://healthcaretransformers.com/digital-health/artificial-intelligence-diagnostics/, 11 October 2021.
  14. S. P. Santhoshkumar, H. Lilly Beaulah, Abdulrahman Saad Alqahtani, P. Parthasarathy, Azath Mubarakali, "A remote diagnosis of Parkinson's ailment using artificial intelligence based BPNN framework and cloud based storage architecture for securing data in cloud environment for the application of telecommunication technologies", Computational Intelligence, https://doi.org/10.1111/coin.12508, 15 February 2022.
  15. S. P. Santhoshkumar, K. Susithra, T. Krishna Prasath3, "An Overview of Artificial Intelligence Ethics: Issues and Solution for Challenges in Different Fields", Journal of Artificial Intelligence and Capsule Networks (ISSN: 2582-2012), Volume 5, Issue 1, Pages 69-86, March 2023.
  16. Most Promising Applications of Artificial Intelligence (AI) in Healthcare Segment https://www.delveinsight.com/blog/top-applications-of-artificial-intelligence-in-healthcare.