Utilization of Artificial Intelligence in Disease Prevention: Diagnosis, Treatment, and Implications for the Healthcare Workforce

• Published in: Healthcare (Basel) Vol. 10; no. 4; p. 608
• Main Authors: Wani, Shahid Ud Din, Khan, Nisar Ahmad, Thakur, Gaurav, Gautam, Surya Prakash, Ali, Mohammad, Alam, Prawez, Alshehri, Sultan, Ghoneim, Mohammed M, Shakeel, Faiyaz
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 24.03.2022; MDPI
• Subjects: 20th century; Accuracy; Algorithms; Artificial intelligence; Asymptomatic; computer methods; COVID-19; Datasets; Deep learning; Disease; disease treatment; Epidemics; Health care industry; healthcare; infectious disease; Influenza; Internet of Things; Language; Machine learning; Medical diagnosis; Natural language processing; Neural networks; Pandemics; Review; Support vector machines; Voice recognition; disease treatment; computer methods; infectious disease; artificial intelligence; healthcare
• ISSN: 2227-9032; 2227-9032
• DOI: 10.3390/healthcare10040608

Artificial intelligence (AI) has been described as one of the extremely effective and promising scientific tools available to mankind. AI and its associated innovations are becoming more popular in industry and culture, and they are starting to show up in healthcare. Numerous facets of healthcare, as well as regulatory procedures within providers, payers, and pharmaceutical companies, may be transformed by these innovations. As a result, the purpose of this review is to identify the potential machine learning applications in the field of infectious diseases and the general healthcare system. The literature on this topic was extracted from various databases, such as Google, Google Scholar, Pubmed, Scopus, and Web of Science. The articles having important information were selected for this review. The most challenging task for AI in such healthcare sectors is to sustain its adoption in daily clinical practice, regardless of whether the programs are scalable enough to be useful. Based on the summarized data, it has been concluded that AI can assist healthcare staff in expanding their knowledge, allowing them to spend more time providing direct patient care and reducing weariness. Overall, we might conclude that the future of "conventional medicine" is closer than we realize, with patients seeing a computer first and subsequently a doctor.