ROLE OF COMPUTATIONAL METHODS FOR ARTIFICAL INTELLIGENCE BASED HEALTHCARE ENGINEERING – A SYSTEMATIC REVIEW

Abstract

Background: Health care has changed because of technological developments, which have improved patient care and diagnoses through telemedicine and diagnostic support systems. These technologies lower costs and improve the quality of care. Healthcare is starting to use artificial intelligence (AI) and associated technologies, which are becoming increasingly common in society and business. Numerous studies have already shown that AI can perform critical healthcare jobs, such as disease diagnosis, on par with or even better than humans. These days, computers are already better than radiologists at identifying dangerous tumors and helping researchers create cohorts for expensive clinical studies. However, we think it will be several years before AI takes the role of humans in many medical process sectors due to several factors. In this article, we discuss AI in healthcare, as well as the potential of AI to automate certain aspects of care. Material and Methods: Major databases such as Medline were explored detailed literature search in resulting in a systematic review pertaining to Computational methods for AI-based healthcare Engineering. Results: Nine original research scientific articles dated between 2020 – 2024 pertaining to mentioned topic were highlighted. Conclusions: In every aspect of healthcare, the use of AI has shown great promise. Additionally, it makes disease diagnosis, decision-making, therapy, and surgery easier for both patients and professionals. The creation of straightforward, reasonably priced, and easily accessible AI-based health solutions could eliminate this disparity. A system like this would aid in achieving the Sustainable Development Goal of encouraging everyone to lead healthy lives. Detailed information regarding the Computational methods for AI-based healthcare Engineering is discussed in this systematic review.