CFP last date
22 July 2024
Call for Paper
August Edition
IJCA solicits high quality original research papers for the upcoming August edition of the journal. The last date of research paper submission is 22 July 2024

Submit your paper
Know more
The week's pick
Responsive image
A semi-parallel data acquisition method in electrical impedance tomography using undersampling technique

Adriano Regis Daniel J. Pagano Francisco R.M. Mota Marduck M. Henao
Random Articles
Reseach Article

Revolutionizing Healthcare through Generative AI: Advancements in Medical Imaging, Drug Discovery, and Data Augmentation

by Waasi Ahmed Jagirdar, Muskaan Rafique Jamal
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 41
Year of Publication: 2023
Authors: Waasi Ahmed Jagirdar, Muskaan Rafique Jamal
10.5120/ijca2023923212

Waasi Ahmed Jagirdar, Muskaan Rafique Jamal . Revolutionizing Healthcare through Generative AI: Advancements in Medical Imaging, Drug Discovery, and Data Augmentation. International Journal of Computer Applications. 185, 41 ( Nov 2023), 16-21. DOI=10.5120/ijca2023923212

@article{ 10.5120/ijca2023923212,
author = { Waasi Ahmed Jagirdar, Muskaan Rafique Jamal },
title = { Revolutionizing Healthcare through Generative AI: Advancements in Medical Imaging, Drug Discovery, and Data Augmentation },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2023 },
volume = { 185 },
number = { 41 },
month = { Nov },
year = { 2023 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number41/32960-2023923212/ },
doi = { 10.5120/ijca2023923212 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:28:20.483442+05:30
%A Waasi Ahmed Jagirdar
%A Muskaan Rafique Jamal
%T Revolutionizing Healthcare through Generative AI: Advancements in Medical Imaging, Drug Discovery, and Data Augmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 41
%P 16-21
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Generative Artificial Intelligence (Generative AI) has emerged as a disruptive force in the healthcare business, promising revolutionary breakthroughs in a variety of fields. This paper delves into the underlying concepts of Generative AI and its medical applications. We look at the benefits, such as efficiency and precision, while also discussing the ethical issues of data privacy and prejudice. We demonstrate how Generative AI is altering medical imaging, medication discovery, and personalized patient care through case studies. We talk about implementation tactics and how to overcome obstacles. Finally, we look ahead, forecasting current trends and innovations that will define the future of healthcare. Generative AI has the potential to reshape the medical age by improving diagnosis, treatment, and patient outcomes.

References
  1. S. Mondal, S. Das, V.G Vrana, How to bell the cat? A theoretical review of generative artificial intelligence towards digital disruption in all walks of life, Technologies 11 (2) (2023) 44.
  2. S. Pal, T. Rabehaja, M. Hitchens, A. Hill, On the design of a flexible delegation model for the Internet of Things using blockchain, IEEE Trans. Ind. Inf. 16 (5) (2019) 3521–3530. M. Jovanovic, M. Campbell, Generative artificial intelligence: trends and prospects, Computer (Long Beach Calif) 55 (10) (2022) 107–112.
  3. J. Perkins, Immersive metaverse experiences in decentralized 3d virtual clinical spaces: artificial intelligence-driven diagnostic algorithms, wearable internet of medical things sensor devices, and healthcare modeling and simulation tools, Am. J. Med. Res. 9 (2) (2022) 89–104.
  4. Gill S.S., Kaur R. ChatGPT: vision and challenges. Internet of Things and Cyber-Physical Systems, 2023.
  5. Q. Cai, H. Wang, Z. Li, X. Liu, A survey on multi-modal data-driven smart healthcare systems: approaches and applications, IEEE Access 7 (2019) 133583–133599.
  6. Y. Guo, T. Yu, J. Wu, Y. Wang, S. Wan, J. Zheng, Q. Dai, Artificial Intelligence for Metaverse: a Framework, CAAI Artif. Intell. Res. 1 (1) (2022) 54–67.
  7. P.P Ray, ChatGPT: a comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope, Internet Things Cyber-Phys. Syst. (2023).
  8. A. Baía Reis, M Ashmore, From video streaming to virtual reality worlds: an academic, reflective, and creative study on live theatre and performance in the metaverse, Int. J. Performance Arts Digital Media 18 (1) (2022) 7–28.
  9. A.A Gaafar, Metaverse in architectural heritage documentation & education, Adv. Ecol. and Environ. Res. 6 (10) (2021) 66–86.
  10. R Godwin-Jones, Emerging spaces for language learning: AI bots, ambient intelligence, and the metaverse, Lang. Learn. Technol. 27 (2) (2023) 6–27.
  11. W.M. Lim, A. Gunasekara, J.L. Pallant, J.I. Pallant, E. Pechenkina, Generative AI and the future of education: ragnarök or reformation? A paradoxical perspective from management educators, Int. J. Manage. Edu. 21 (2) (2023) 100790.
  12. M. Poggi, F. Tosi, K. Batsos, P. Mordohai, S. Mattoccia, On the synergies between machine learning and binocular stereo for depth estimation from images: a survey, IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2021) 5314–5334.
  13. W.K. Sleaman, A.A. Hameed, A. Jamil, Monocular vision with deep neural networks for autonomous mobile robots navigation, Optik (Stuttg) 272 (2023) 170162.
  14. X. Guo, Z. Wang, W. Zhu, G. He, H.B. Deng, C.X. Lv, Z.H Zhang, Research on DSO vision positioning technology based on binocular stereo panoramic vision system, Defence Technol. 18 (4) (2022) 593–603.
  15. F. Andriulli, P.Y. Chen, D. Erricolo, J.M Jin, Guest editorial machine learning in antenna design, modeling, and measurements, IEEE Trans. Antennas Propag. 70 (7) (2022) 4948–4952.
  16. X. Wu, F. Guan, A. Xu, Passive ranging based on planar homography in a monocular vision system, J. Info. Process. Syst. 16 (1) (2020) 155–170.
  17. F. Gao, C. Wang, L. Li, Altitude information acquisition of uav based on monocular vision and mems, J. Intell. Robotic Syst. 98 (2020) 807–818.
  18. R.M. Samant, M.R. Bachute, S. Gite, K. Kotecha, Framework for deep learning-based language models using multi-task learning in natural language understanding: a systematic literature review and future directions, IEEE Access 10 (2022) 17078–17097.
  19. D. Ai, G. Jiang, S.K. Lam, C. Li, Computer vision framework for crack detection of civil infrastructure—A review, Eng. Appl. Artif. Intell. 117 (2023) 105478.
  20. M. Hawkins, Metaverse live shopping analytics: retail data measurement tools, computer vision and deep learning algorithms, and decision intelligence and modeling, J. Self-Governance Manage. Econ. 10 (2) (2022) 22–36.
  21. R. Watson, The virtual economy of the metaverse: computer vision and deep learning algorithms, customer engagement tools, and behavioral predictive analytics, Linguistic Philos. Investig. (21) (2022) 41–56.
  22. M. Hawkins, Virtual employee training and skill development, workplace technologies, and deep learning computer vision algorithms in the immersive metaverse environment, Psychosociological Issues Human Resour. Manage. 10 (1) (2022) 106–120.
  23. S. Gordon, Virtual navigation and geospatial mapping tools, customer data analytics, and computer vision and simulation optimization algorithms in the blockchain-based metaverse, Rev. Contemp. Philos. (21) (2022) 89–104.
  24. G.H. Popescu, K. Valaskova, J. Horak, Augmented reality shopping experiences, retail business analytics, and machine vision algorithms in the virtual economy of the metaverse, J. Self-Governance Manage. Econ. 10 (2) (2022) 67–81.
Index Terms

Computer Science
Information Sciences

Keywords

Generative AI Medical Era Healthcare Medical Imaging Drug Discovery Patient Care Ethical Considerations Future Trends

Powered by PhDFocusTM