Machine learning algorithms for smart and intelligent healthcare system in Society 5.0. Issue 12 (17th October 2022)

• Record Type: Journal Article
• Authors: Zamzami, Ikhlas Fuad; Pathoee, Kuldeep; Gupta, Brij B.; Mishra, Anupama; Rawat, Deepesh; Alhalabi, Wadee
• Is Part Of: International journal of intelligent systems. Volume 37:Issue 12(2022)
• Page Start: 11742
• Page End: 11763
• Publication Date: 2022-10-17
• Subjects: machine learning -- smart health care systems -- Society 5.0; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.23061
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: The pandemic has shown us that it is quite important to keep track record our health digitally. And at the same time, it also showed us the great potential of Instruments like wearable observing gadgets, video conferences, and even talk bots driven by artificial intelligence (AI) can provide good care from remotely. Real time data collected from different health care devices of cases across globe played an important role in combatting the virus and also help in tracking its progress. The evolution of biomedical imaging techniques, incorporated sensors, and machine learning (ML) in recent years has led in various health benefits. Medical care and biomedical sciences have become information science fields, with a solid requirement for refined information mining techniques to remove the information from the accessible data. Biomedical information contains a few difficulties in information investigation, including high dimensionality, class irregularity, and low quantities of tests. AI is a subfield of AI and computer science which centric the utilization of information and calculations to impersonate the way that people learn, steadily further developing its accuracy. ML is an essential element of the rapidly growing area of information science. Calculations are created using measurable procedures to make characterizations or forecasts, exposing vital experiences inside information mining operations. In this chapter, we explain and compare the different algorithms of ML which could be helpful in detecting different disease at earlier stage. We summarize the algorithms and different steps involved in ML to extract information for betterment of the society which is already exposed to the world of data.