Artificial intelligence in acute respiratory distress syndrome: A systematic review

Background and objective: Acute respiratory distress syndrome (ARDS) is a life-threatening pulmonary disease with a high clinical and cost burden across the globe. Artificial intelligence (AI), an emerging area, has been used for various purposes in ARDS. We aim to summarize the currently available literature on various applications of AI in ARDS through a systematic review. Methodology: PubMed was searched from inception to February 2021 to collate all the studies. Additionally, a bibliographic search of included studies and a random search on Google, Google Scholar, and Research Gate were performed to identify relevant articles. Studies published in English language that employed data about developing and/or assessing the role of AI in the various aspects of ARDS were considered for this review. Three independent reviewers performed study selection and data extraction; any disagreements were settled through consensus or discussion with another member of the research team. Results: A total of 19 studies published between the year 2002 and 2020 were included. In these included studies, AI was used for various purposes in ARDS such as diagnosis (n = 10; 53 %), risk stratification (n = 1; 5 %), prediction of severity (n = 3; 17 %), management (n = 2; 10 %), prediction of mortality (n = 2; 10 %), and decision making (n = 1; 5 %). The area under the curve among the developed models in the included studies ranged between 0.8 and 1, which is considered to be very good to excellent. Conclusion: AI is revolutionizing healthcare and has a wide range of applications in ARDS, such as minimizing cost and enhancing outcomes.