SCCM Resource Library-The Future of AI in Critical Care: A Tsunami of Predictions or a Consensus of Opinions?

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The document summarizes the potential impact of artificial intelligence (AI) and machine learning in critical care, featuring insights from Dr. Gari D. Clifford. It draws parallels between the public mistrust of self-driving vehicles and similar skepticism towards AI in healthcare, while pointing out that AI technologies, like autonomous cars, can significantly enhance safety and efficacy.<br /><br />Dr. Clifford highlights that medical errors are a leading cause of death in the U.S., suggesting that AI can enhance healthcare delivery by reducing such errors. AI, particularly machine learning and deep learning, uses data and algorithms to mimic human learning processes, potentially improving healthcare outcomes. The development of advanced technologies like graphics processing units (GPUs) has democratized AI, making it more accessible. While deep learning allows for the discovery of complex data patterns, Dr. Clifford warns of the risks associated with low-quality data, which can lead to unreliable results.<br /><br />In critical care, AI is seen as an assistant to healthcare professionals rather than a replacement. Dr. Clifford advocates for AI's role as an assistive technology, enhancing clinical decision-making. Through competitions like those organized by PhysioNet, researchers aim to crowdsource solutions for predicting medical conditions like sepsis, akin to weather modeling for hurricanes. Combining different AI models can improve predictive accuracy, but the timing of predictions is pivotal to their utility. <br /><br />Dr. Clifford encourages viewing AI as a team member in the medical field, emphasizing collaboration between humans and technology for improved patient care. Institutions like Sound Physicians are actively incorporating AI-driven innovations in critical care, offering enhanced career growth, leadership development, and flexible opportunities for healthcare professionals.

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Professional Development and Education, 2022, 0:07:41

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This article was first published in the Summer 2022 issue of Critical Connections.

In 2020, Gari D. Clifford, DPhil, MA, MSc, SMIEEE, spoke on the mistrust and concerns over self-driving cars as part of a larger conversation about artificial intelligence (AI) during a Congress plenary session “The Future of AI in Critical Care: A Tsunami of Predictions or a Consensus of Opinions?” The article reflects on those concepts and offers updates. Throughout his career, he has explored concerns about the budding technology and examples of how AI can help critical care professionals moving forward.

Critical Connections, the critical care industry's only magazine, provides information in cutting-edge topics in critical care useful to the entire multiprofessional team.

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Meta Tag

Content Type Article

Knowledge Area Professional Development and Education

Knowledge Level Foundational

Knowledge Level Intermediate

Knowledge Level Advanced

Membership Level Associate

Membership Level Professional

Membership Level Select

Tag Innovation

Year 2022

Keywords

artificial intelligence

machine learning

critical care

Dr. Gari D. Clifford

healthcare

medical errors

deep learning

predictive accuracy

assistive technology

AI-driven innovations

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