Intelligence Artificielle vue de l'anesthésie réanimation
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The document discusses the integration of artificial intelligence in anesthesiology and critical care, emphasizing the importance of advanced simulation programs and global education to enhance medical training. It highlights the need for smarter healthcare information systems to manage the increasing volume of clinical data, aiming to improve decision-making and patient care. By focusing on evolving educational methods and AI technologies, the initiative seeks to address physician shortages and optimize healthcare delivery.
Intelligence Artificielle vue de l'anesthésie réanimation
- 1. Pr Alexandre MIGNON Port-Royal Cochin AP-HP Université Sorbonne Paris Cité alexandre.mignon@ilumens.org Intelligence Artificielle Vue de l’anesthésie réanimation Alexandre Mignon @iLumens @ampcmignon
- 5. MOOC (Massive Open-Online Courses) OER (Open Educational Resources) … 1 LMS (Learning Managing System) Platforms, SCORM Networks, Communities 3 Blended Learning PBLD (Problem Based Learning Discussion) OSCE (Objective Structured Clinical Examination) Simulation 2 Flipped Classroom
- 6. AI in Medicine grows rapidly Pubmed cites to "Artificial Intelligence" 0 500 1000 1500 2000 2500 3000 3500 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Year NumberofCitations
- 8. Escalating amount of information that doctors have to deal with everyday Physician shortage, Costs, Search for “Humanism” Perform diagnosis Make therapy recommendations Critical care is the permanent and thorough care provided to the critical patients in intensive care units, with constant monitoring Early Warning Scores DATA JAMA 26 oct 2017 Rapid decisions Large and disparate array of information AI : simultaneously gather and display multiple physiological signals, derive clinically important parameters, and generate alerts JAMA Dec 2016
- 9. • Making Health Information Systems Smarter and More Usable Clinical Data are Mostly Text • Need Text Understanding – Discharge summaries – Clinical notes (admitting, doctors’, nurses’, …) – Reports (radiology, pathology, …) – Letters • Exceptions : – Lab data – Pharmacy orders – Billing codes – Images (but, need image understanding)