Home / Current Issue / Paper 1704264
AI in Healthcare Services
Subject area: Science,Engineering and Technology · Area of research: Healthcare
Abstract
In this study, we aim to provide a narrative overview of healthcare services that use artificial intelligence (AI)-based services as part of operations and evaluate the key factors for creating effective AI-based healthcare services. How artificial intelligence improves health care outcomes, helps caregivers at work and reduces health care costs is used to quantify the benefits of artificial intelligence in health care. With a 28% global compound annual growth rate, the AI market in the healthcare sector also has significant market potential. This research will bring together insights from many aspects of the healthcare sector, such as finance, health improvement and care outcomes, as well as provide recommendations and highlight key elements for the effective use of artificial intelligence techniques in the medical field. This study shows how using artificial intelligence in healthcare can reduce costs while improving everyone's health. The method adopted for data collection required for this research is the Survey Method and use of secondary data available. The Survey Method proved to be instrumental in framing the respondent profile and also in realizing their opinions on AI in Healthcare Services.
Keywords
Artificial Intelligence, Healthcare Analytics, Machine Vision, Machine Learning, Healthcare Applications, Text Mining, and Administrative Applications.
References
[1] Tran BX, Vu GT, Ha GH, Vuong Q-H, Ho M-T, Vuong T-T, et al. Global evolution of research in artificial intelligence in health and medicine: a bibliometric study. J Clin Med. 2019; 8(3):360.
[2] Zupic I, Čater T. Bibliometric methods in management and organization. Organ Res Methods. 2015; 1(18):429–72.
[3] Secinaro S, Calandra D. Halal food: structured literature review and research agenda. Br Food J. 2020. https://doi.org/10.1108/BFJ-03-2020-0234.
[4] Rialp A, Merigó JM, Cancino CA, Urbano D. Twenty-five years (1992–2016) of the international business review: a bibliometric overview. Int Bus Rev. 2019; 28(6):101587.
[5] Zhao L, Dai T, Qiao Z, Sun P, Hao J, and Yang Y. Application of artificial intelligence to wastewater treatment: a bibliometric analysis and systematic review of technology, economy, management, and wastewater reuse. Process Saf Environ Prot. 2020; 1(133):169–82.
[6] Huang Y, Huang Q, Ali S, Zhai X, Bi X, Liu R. Rehabilitation using virtual reality technology: a bibliometric analysis, 1996–2015. Scientometrics. 2016; 109(3):1547–59.
[7] Hao T, Chen X, Li G, Yan J. A bibliometric analysis of text mining in medical research. Soft Comput. 2018; 22(23):7875–92.
[8] Dos Santos BS, Steiner MTA, Fen Erich AT, Lima RHP. Data mining and machine learning techniques applied to public health problems: a bibliometric analysis from 2009 to 2018. Comput Ind Eng. 2019; 1(138):106120.
[9] Liao H, Tang M, Luo L, Li C, Chiclana F, Zeng X-J. A bibliometric analysis and visualization of medical big data research. Sustainability. 2018; 10(1):166.
[10] Choudhury A, Renjilian E, Asan O. Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review. JAMIA Open. 2020; 3(3):459–71.
[11] Connelly TM, Malik Z, Sehgal R, Byrnes G, Coffey JC, Peirce C. The 100 most influential manuscripts in robotic surgery: a bibliometric analysis. J Robot Surg. 2020; 14(1):155–65.
[12] Guo Y, Hao Z, Zhao S, Gong J, Yang F. Artificial intelligence in health care: bibliometric analysis. J Med Internet Res. 2020; 22(7):e18228
[13] Choudhury A, Asan O. Role of artificial intelligence in patient safety outcomes: systematic literature review. JMIR Med Inform. 2020; 8(7):e18599.
[14] Tagliaferri SD, Angelova M, Zhao X, Owen PJ, Miller CT, Wilkin T, et al. Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews. NPJ Digit Med. 2020; 3(1)
[15] www.foreseemed.com/artificial-intelligence-in-healthcare
[16] https://www.arm.com/glossary/ai-in-healthcare
[17] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616181/
[18] https://www.ibm.com/in-en/topics/artificial-intelligence-healthcare
[19] https://www.google.com/search?q=ai+in+healthcare&sxsrf
[20] https://www.analyticssteps.com/blogs/role-artificial-intelligence-healthcare
[21] https://www.novatiosolutions.com/
[22] https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-021-01488-9
[23] https://www.entrepreneur.com/en-in/technology/artificial-intelligence-and-its-role-in-healthcare/427963
[24] https://www2.deloitte.com/us/en/pages/life-sciences-and-health-care/articles/future-of-artificial-intelligence-in-health-care.html
[25] https://intellipaat.com/blog/artificial-intelligence-in-healthcare/
[26] https://emeritus.org/blog/healthcare-challenges-of-ai-in-healthcare/
[27] https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-019-1426-2
[28] https://research.aimultiple.com/challenges-of-ai-in-healthcare/
[29] https://www.forbes.com/sites/forbesbusinesscouncil/2023/02/07/top-five-opportunities-and-challenges-of-ai-in-healthcare/
[30] https://www.intuitive.com/en-us/patients/da-vinci-robotic-surgery/about-the-systems
How to cite this paper
@article{1704264,
author = {Sujay Samanta, Harsh Gupta, R L Nidhi, Arihant Rathod, Nitaichandra Paraddi; Dr. Anita Walia},
title = {AI in Healthcare Services},
journal = {Iconic Research And Engineering Journals},
year = {2023},
volume = {6},
number = {10},
pages = {225-242},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1704264.pdf},
abstract = {In this study, we aim to provide a narrative overview of healthcare services that use artificial intelligence (AI)-based services as part of operations and evaluate the key factors for creating effective AI-based healthcare services. How artificial intelligence improves health care outcomes, helps caregivers at work and reduces health care costs is used to quantify the benefits of artificial intelligence in health care. With a 28% global compound annual growth rate, the AI market in the healthcare sector also has significant market potential. This research will bring together insights from many aspects of the healthcare sector, such as finance, health improvement and care outcomes, as well as provide recommendations and highlight key elements for the effective use of artificial intelligence techniques in the medical field. This study shows how using artificial intelligence in healthcare can reduce costs while improving everyone's health. The method adopted for data collection required for this research is the Survey Method and use of secondary data available. The Survey Method proved to be instrumental in framing the respondent profile and also in realizing their opinions on AI in Healthcare Services.},
keywords = {Artificial Intelligence, Healthcare Analytics, Machine Vision, Machine Learning, Healthcare Applications, Text Mining, and Administrative Applications.},
month = {April},
}