Utilizing Artificial Intelligence in Critical Care: Adding A Handy Tool to Our Armamentarium

As per the definition found in Britannica by Copeland, AI is commonly referred to as a computer system with human intellectual features, e.g., reasoning, discovering, generalizing, and learning from prior exposure [1,2]. U.S Food and Drug Administration (US-FDA) has also stated in 2019 that AI has the potential to transform the healthcare industry by its ability to derive new information from the vast dataset that feeds into it [2,3]. Machine learning (ML) can be simply understood as a subset of an application of AI in which machines analyze and use a large dataset to produce unique algorithms capable of "statistical learning" as described by Gutierrez [2]. The use of ML has surged in critical care in the field of the discovery of drugs, diagnostic tools, medical imaging, and therapeutics amongst others. It can potentially help us better understand the vast set of data available to us in an intensive care unit (ICU) and apply it to tackle a multitude of medical conditions [2,4]. ML can be divided into two main models based on learning tasks, which are supervised and unsupervised learning algorithms.