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EP080 Artificial intelligence in regional anesthesia: current utility and limitations: Making Regional anesthesia powered by AI
  1. Chitrambika P Krishna Das M1,2 and
  2. Yasser Mohamed Reda Abass Toble3
  1. 1Resident anesthesia , Hamad medical corporation Al Rayyan Doha Qatar , Doha Qatar , Qatar
  2. 2Resident anesthesia , ESI BasaiDarapur New Delhi India , Delhi, India
  3. 3Senior Consultant Anesthesia v, Hamad medical corporation, Doha, Qatar


Background and Aims Artificial intelligence (A.I.) is now an integral part of our day-to-day life. Starting from voice recognition on devices to automated chat box responds AI has innovated our households as well as work. There are possibilities of AI to revolutionize future practice of ultrasound guided regional anesthesia (USRA) through supporting ultrasound scanning. This could help with improved patient outcomes, interpersonal variability, and time requirement. we intend to review the current literature in AI practiced and established in UGRA as well as look at the new advances.

Methods We reviewed articles published in last 6 years about AI in Ultra sounded regional anesthesia as well as needed cross references for better understandings of the innovative topic involving. Quality of the studies in terms of RCT, Comparative analysis observational and cohort were individually assessed according to the methodology followed (total of 14) and metanalysis (1).

Results The results were elaborated in regard to specific AI technology used: Color Over lay (ScanNavTm) overlay, Deep learning, CNN network (needle tracking) and outcome utility discussed individually. Also AI utility in Medical education of Tranee for USGRA was assessed as a component of the outcome measures.

Abstract EP080 Figure 1

Scan nav color over lay

Abstract EP080 Figure 2

CNN needle tracking

Abstract EP080 Figure 3

Deep learning network

Conclusions AI in USGRA review demonstrate a steep improvement in patient outcome and procedural ease with use of AI. Also, as a tool to administer step to step feedback in medical training for peripheral nerve block. It Tremendously improved US image correct identification and enhances needle tracking. Hence reducing inadvertent Nerve injury, vascular trauma or systemic toxicity of local anesthetic medication.

  • AI
  • Machene learning
  • Scannav

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