USING ARTIFICIAL INTELLIGENCE (AI)TECHNOLOGY IN THE HEALTH SECTOR HASSEVERAL GOALS
Keywords:
Goals, Machine Learning, Healthcare, Artificial intelligence (AI), Technologies, Chronic DiseasesAbstract
In a broad sense, artificial intelligence (AI) refers to any computer or system behavior that resembles human behavior.A subfield of artificial intelligence called "machine learning" enables computers to learn from data without explicit human programming.One of the most significant contemporary trends in global healthcare is the use of artificial intelligence(AI) technologies in medicine.Technologies based on artificial intelligence are profoundly transforming the world's healthcare system, enabling a dramatic reconstruction of the medical diagnostics system while simultaneously lowering healthcare expenditures. Identifying the class of diseases to
which a disease belongs is crucial before treating it. It is feasible to categorize the type of disease based on the feature space of the condition. Algorithms for machine learning can address this issue.
References
Liu, Jiaying & Kong, Xiangjie & Xia, Feng & Bai,Xiaomei & Wang, Lei & Qing, Qing & Lee, Ivan.(2018). Artificial Intelligence in the 21st Century. IEEE Access. PP. 1-1. 10.1109/ACCESS.2018.2819688
R. M. Fazliddinovich and B. U. Abdumurodovich, "Parallel processing capabilities in the process of speechrecognition," 2017 International Conference on Information Science and Communications Technologies(ICISCT), 2017, pp. 1-3, doi: 10.1109/ICISCT.2017.8188585.
M. Musaev, I. Khujayorov and M. Ochilov, "Development of integral model of speech recognition systemfor Uzbek language," 2020 IEEE 14th International Conference on Application of Information andCommunication Technologies (AICT), 2020, pp. 1-6.
M. Rakhimov, J. Elov, U. Khamdamov, S. Aminov and S. Javliev, "Parallel Implementation of Real-TimeObject Detection using OpenMP," 2021 International Conference on Information Science andCommunications Technologies (ICISCT), 2021, pp. 1-4, doi: 10.1109/ICISCT52966.2021.9670146.
Khdier, Hajer & Jasim, Wesam & Aliesawi, Salah. (2021). Deep Learning Algorithms based VoiceprintRecognition System in Noisy Environment. Journal of Physics: Conference Series. 1804. 012042.10.1088/1742-6596/1804/1/012042.
Mihret, Estifanos. (2020). Robotics and Artificial Intelligence. International Journalof Artificial Intelligenceand Machine Learning. 10. 10.4018/IJAIML.2020070104.
M. Musaev and M. Rakhimov, "Accelerated Training for Convolutional Neural Networks," 2020International Conference on Information Science and Communications Technologies (ICISCT), 2020, pp.1-5, doi:10.1109/ICISCT50599.2020.9351371.
Brown, Carol & O'Leary, Daniel. (1995). Introduction to artificial intelligence and expert systems. ArtificialIntelligence/Expert Systems Section of the American Accounting Association.
Kashyap, Abhishek. (2018). Artificial Intelligence & Medical Diagnosis. 6. 4982-4985.
21276/sjams.2018.6.12.61.
Artificial Intelligence Index Report 2022. Chapter 4: The Economy and Education. 4.2 Investment.
https://aiindex.stanford.edu/wpcontent/uploads/2022/03/2022-AI-Index-Report_Master.pdf[11] ?awrynowicz, Agnieszka & Tresp, Volker. (2014). Introducing Machine Learning.
Cunningham, Padraig & Delany, Sarah. (2007). k-Nearest neighbour classifiers. Mult Classif Syst.
10.1145/3459665.
M. Rakhimov, T. Boburkhon and T. Khurshid, "Speaker Separation: Use Neural Networks," 2021
International Conference on Information Science and Communications Technologies (ICISCT), 2021, pp.01-03, doi:10.1109/ICISCT52966.2021.9670322.
M. Rakhimov and M. Ochilov, "Distribution of Operations in Heterogeneous Computing Systems for
Processing Speech Signals," 2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT), 2021, pp. 1-4, doi: 10.1109/AICT52784.2021.9620451.
M. Musaev and M. Rakhimov, "A Method of Mapping a Block of Main Memory to Cache in ParallelProcessing of the Speech Signal" 2019 International Conference on Information Science andCommunications Technologies (ICISCT), 2019, pp. 1-4, doi: 10.1109/ICISCT47635.2019.9011946.
M. Rakhimov, D. Mamadjanov and A. Mukhiddinov, "A HighPerformance Parallel Approach to ImageProcessing in Distributed Computing," 2020 IEEE 14th International Conference on Application ofInformation and Communication Technologies (AICT), 2020, pp. 1-5, doi:10.1109/AICT50176.2020.9368840.
Ma, Jabbar. ?Prediction of heart disease using k-nearest neighbor and particle swarm optimization.?
Biomedical Research-tokyo 28 (2017): 4154-4158.
Alpaydin, E. Voting over Multiple Condensed Nearest Neighbors. Artificial Intelligence Review 11, 115–132 (1997).
Jabbar MA, Deekshatulu BL, Priti C. Heart disease classification using nearest neighbor classifier withfeature subset selection. AnnalsComputer Science 2013.
W. Xing and Y. Bei, "Medical Health Big Data Classification Based on KNN Classification Algorithm," inIEEE Access, vol. 8, pp. 28808-28819, 2020, doi: 10.1109/ACCESS.2019.2955754.
https://www.cdc.gov/nchs/fastats/heart-disease.htm [22] Huang, Nur & Ibrahim, Zaidah & Diah, Norizan.(2021). Machine Learning Techniques for Heart Failure Prediction. MALAYSIAN JOURNAL OFCOMPUTING. 6. 872. 10.24191/mjoc.v6i2.13708.
M. Rakhimov, R. Akhmadjonov, S. Javliev, ?Artificial Intelligence in Medicine for Chronic DiseaseClassification Using Machine Learning?, at:https://www.researchgate.net/publication/367194708, ·
October 2022, DOI: 10.1109/AICT55583.2022.10013587.
T. M. Tassew, X. Nie, ?A Comprehensive Review of the Application of Machine Learning in Medicine andHealth Care?, A Comprehensive Review of the Application of Machine Learning in Medicine and Health
Care. TechRxiv. Preprint.https://doi.org/10.36227/techrxiv.21204779.v1, 2022.
F. Del Giorgio Solfa, & F. R. Simonato, ?Big Data Analytics in Healthcare: Exploring the Role of MachineLearning in Predicting Patient Outcomes and ImprovingHealthcare Delivery?, International Journal ofComputations Information and Manufacturing (IJCIM) · June 2023, at:
https://www.researchgate.net/publication/371804162.
M. A. Baballe, A.M. Gambale, A. S. Bari, A. S. Lawan, & R. J. Suleiman. (2022). Issues with ourhospitals queue management information systems. Global Journal of Research in Medical Sciences, 2(6),
–106.https://doi.org/10.52 81/zenodo.7330904.
A. H. Muhammad, A. Y. Abdullahi, A. Abba, A. Isah, A. A Yako, M. A. Baballe, ?The Benefits ofAdopting a Wireless Nurse Call System?, Global Journal of Research in Medical Sciences Volume 02 |
Issue 03 | May-June | 2022 Journal homepage:https://gjrpublication.com/gjrms/.
Mehta V. ?Artificial Intelligence in Medicine: Revolutionizing Healthcare for Improved PatientOutcomes?, J Med Res Innov. 2023, 7(2), DOI: 10.32892/jmri.292.
A. Naveed, ?Transforming Healthcare through Arti?cial Intelligence and Machine Learning?, PAKISTANJOURNAL OF HEALTH SCIENCES,https://thejas.com.pk/index.php/pjhs, Volume 4, Issue 5 May2023.
R.J.Woodman, A.A.Mangoni, ?A comprehensive review ofmachine learning algorithms andtheir
application ingeriatric medicine: present andfuture?, Aging Clinical and Experimental Research, 2023,https://doi.org/10.1007/s40520-023-02552-2.
Y.S Cho, P. C, Hong, ?Applying Machine Learning to Healthcare Operations Management: CNN-BasedModel for Malaria Diagnosis?, Healthcare (MDPI), 2023, 11, 1779. https://doi.org/10.3390/healthcare11121779.
M. A. Baballe, A. S. Muhammad, J. Y. Abdullahi, Aminu Ya'u,, Ibrahim Idris Giwa, M. Habib Abubakar,& Z. Abdulkadir. (2022). The Impact of Hospital Queue Management Systems. Global Journal of Research
in Medical Sciences, 2(5), 88–91.https://doi.org/10.5281/zenodo.7117651.
S. Brown, "Machine learning, explained.," MIT Sloan School Of Management, 21:(04) 2021. [Online].Available:https://mitsloan.mit.edu/ideas-made-to-matter/machine.
Muhammad A. B.,& Mukhtar I. B. (2023). Artificial Intelligence in the Healthcare Sector. In GlobalJournal of Research in Engineering & Computer Sciences (Vol. 3, Number 5, pp.10–13).
https://doi.org/10.5281/zenodo.100017 67.
https://emeritus.org/blog/healthcare-challenges-of-ai-in-healthcare/.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Author(s) and co-author(s) jointly and severally represent and warrant that the Article is original with the author(s) and does not infringe any copyright or violate any other right of any third parties and that the Article has not been published elsewhere. Author(s) agree to the terms that the IPHO Journal will have the full right to remove the published article on any misconduct found in the published article.
