SCCM Resource Library-Artificial Intelligence in Adult Patient Care

Video Transcription

Video Summary

Machine learning and artificial intelligence (AI) have the potential to greatly improve patient outcomes in critical care. These methods use complex mathematical constructs to capture hidden insights within data that may not be apparent to the human eye. In critical care, AI and machine learning can play a role in early detection of deteriorating patient conditions, such as sepsis, acute kidney injury, and acute respiratory failure. Predictive algorithms, which use retrospective electronic medical record data, have been successful in identifying distress signals earlier than human observation, allowing for earlier intervention and improved outcomes. There has also been progress in using biomarkers and pathogen-based biomarkers for more specific diagnosis and intervention. Additionally, machine learning has been used for phenotyping, clustering patients based on similarities in their conditions to provide personalized care. However, there are challenges in validating these models and translating them to real-world settings, such as reliance on public datasets and the lack of external validation.

Asset Subtitle

Professional Development and Education, 2023

Asset Caption

Type: one-hour concurrent | Artificial Intelligence: Challenges and Opportunities for Critical Care (SessionID 1228616)

Meta Tag

Content Type Presentation

Knowledge Area Professional Development and Education

Membership Level Professional

Membership Level Select

Tag Innovation

Year 2023

Keywords

Machine learning

Artificial intelligence

Critical care

Predictive algorithms

Personalized care

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