Artificial Intelligence and Machine Learning Based Intervention in Medical Infrastructure: A Review and Future Trends

• Published in: Healthcare (Basel) Vol. 11; no. 2; p. 207
• Main Authors: Kumar, Kamlesh, Kumar, Prince, Deb, Dipankar, Unguresan, Mihaela-Ligia, Muresan, Vlad
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 10.01.2023; MDPI
• Subjects: Algorithms; Artificial intelligence; Breast cancer; Cancer therapies; Coronaviruses; COVID-19; Deep learning; Disease; Documentation; Drug dosages; Illnesses; Infrastructure; Laboratories; Ligands; Lung cancer; Machine learning; Medical imaging; Medical research; Pandemics; R&D; Research & development; Review; Robots; Skin cancer; X-rays; deep learning; artificial intelligence in healthcare; medical infrastructure; healthcare infrastructure; machine learning; artificial intelligence; healthcare and AI
• ISSN: 2227-9032; 2227-9032
• DOI: 10.3390/healthcare11020207

People in the life sciences who work with Artificial Intelligence (AI) and Machine Learning (ML) are under increased pressure to develop algorithms faster than ever. The possibility of revealing innovative insights and speeding breakthroughs lies in using large datasets integrated on several levels. However, even if there is more data at our disposal than ever, only a meager portion is being filtered, interpreted, integrated, and analyzed. The subject of this technology is the study of how computers may learn from data and imitate human mental processes. Both an increase in the learning capacity and the provision of a decision support system at a size that is redefining the future of healthcare are enabled by AI and ML. This article offers a survey of the uses of AI and ML in the healthcare industry, with a particular emphasis on clinical, developmental, administrative, and global health implementations to support the healthcare infrastructure as a whole, along with the impact and expectations of each component of healthcare. Additionally, possible future trends and scopes of the utilization of this technology in medical infrastructure have also been discussed.