Title
Current trends on the application of artificial intelligence in medical sciences
Authors
Aisha Mousa Mashraqi 1,* & Budoor Allehyani2
Affiliation
1Department of Computer Science, College of Computer Science and Information Systems, Najran University; 2Department of Information System, College of Computers and Information Systems, Umm Al-Qura University; *Corresponding author
Aisha Mousa Mashraqi - E-mail: Ammashraqi@nu.edu.sa; https://orcid.org/0000-0003-0449-8910
Budoor Allehyani - E-mail: Balehyani@uqu.edu.sa
Article Type
Research Article
Date
Received November 1, 2022; Revised November 29, 2022; Accepted November 30, 2022, Published November 30, 2022
Artificial Intelligence (AI) is expanding with colossal applications in various sectors. In the healthcare sector, it is booming to make life simpler with utmost accuracy by predicting, diagnosing and up to care with the help of Machine Learning (ML) and Deep Learning (DL) applications. Modern computer algorithms have attained accuracy levels comparable to those of human specialists in medical sciences, although computers often do jobs more quickly than people do. It is also expected that there will not be a mandate for humans to be present for the jobs that machines can do, and it is gaining the highest peak because of good trained artificial models in the medical field. ML enhances the therapeutic process and improves health by encouraging more patient participation. ML may get more accurate patient data when used with the Internet of Medical Things (IoMT) and automate message notifications that prompt patients to respond at certain times. The motivation behind this article is to make a comprehensive review of the on-going implementation of ML in medical science, what challenges it is facing now, and how it can be simplified for future researchers to contribute better to medical sciences while applying it to the practitioners' jobs easier. In this review, we have extensively mined the data and brought up systematised applications of AI in healthcare, what challenges have been faced by the experts, and what ethical responsibilities are liable to them while taking the data. We also tabulated which algorithms will be helpful for what kind of data and disease conditions will be useful for future researchers and developers. This article will provide a better insight into AI and ML for the beginner to the advanced developer and researcher to understand the concepts from the basics.
Keywords
Machine Learning; Deep Learning; Disease Diagnosis; Medical Imaging; Drug repurposing.
Citation
Mashraqi et al. Bioinformation 18(11): 1050-1061 (2022)
Edited by
P Kangueane
ISSN
0973-2063
Publisher
License
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
