This study aims to interpret the Bispectral Index (BIS) monitoring method, which we routinely use for monitoring in scoliosis surgery, with artificial intelligence (AI) tools and to determine the accuracy and reliability of AI tools in clinical practice by comparing this interpretation with the interpretations of two clinicians experienced in BIS.
The Bispectral Index (BIS) is an FDA-approved method for monitoring the depth of anesthesia. BIS combines time-domain, frequency-domain, and bispectral analysis of electroencephalography and is displayed as a dimensionless number between 0 (deep anesthesia) and 100 (awake); a value between 40 and 60 is suitable for surgical anesthesia. BIS shows good correlation with hypnotic state and anesthetic drug concentration, and its use can shorten recovery times. Recently, the use of artificial intelligence (AI) tools (Gemini 3.1, ChatCPT 5.5, Copilot 365 Premium) has become widespread in all fields. However, in the medical literature, there are only a limited number of recent studies that aim to enable emergency intervention in patients, increase clinical use, and obtain advice even if treatment recommendations are not available. Therefore, this study aims to interpret the BIS monitoring method, which we routinely use for monitoring in scoliosis surgery, with AI tools and to determine the accuracy and reliability of AI tools in clinical practice by comparing this interpretation with the interpretations of two clinicians experienced in BIS.
Study Type
OBSERVATIONAL
Enrollment
63
CHATGPT responses
GEMİNİ responses
COPİLOT responses
University of Health Sciences, Antalya Training and Research Hospital
Antalya, Muratpaşa, Turkey (Türkiye)
Clinical Experience
The proximity of AI programs to the clinical experience. The study will examine the percentage of times AI programs' interpretations and intervention recommendations regarding information processing stimulus (ISIS) are identical to those of two clinical practitioners.
Time frame: 12 hours
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Clinicians responses