Artificial Intelligence in the Intensive Care Unit: Present and Future in the COVID-19 Era

The development of artificial intelligence (AI) allows for the construction of technologies capable of implementing functions that represent the human mind, senses, and problem-solving skills, leading to automation, rapid data analysis, and acceleration of tasks. These solutions has been initially implemented in medical fields relying on image analysis; however, technological development and interdisciplinary collaboration allows for the introduction of AI-based enhancements to further medical specialties. During the COVID-19 pandemic, novel technologies established on big data analysis experienced a rapid expansion. Yet, despite the possibilities of advancements with these AI technologies, there are number of shortcomings that need to be resolved to assert the highest and the safest level of performance, especially in the setting of the intensive care unit (ICU). Within the ICU, numerous factors and data affect clinical decision making and work management that could be managed by AI-based technologies. Early detection of a patient's deterioration, identification of unknown prognostic parameters, or even improvement of work organization are a few of many areas where patients and medical personnel can benefit from solutions developed with AI.

Automated summary

The development of AI has led to the creation of technologies that replicate human thinking, senses, and problem-solving abilities, resulting in automation, rapid data analysis, and accelerated tasks. These solutions have been initially used in medical fields relying on image analysis but can be further enhanced through AI-based advancements. The COVID-19 pandemic has seen a widespread adoption of novel AI technologies based on big data analysis. However, there are still shortcomings that need to be addressed to ensure the highest level of performance, particularly in intensive care units (ICUs). AI-based technologies have the potential to manage various factors and data affecting clinical decision making and work management in the ICU, such as early detection of patient deterioration, identification of unknown prognostic parameters, and improvement of work organization.