Actively Recruiting

Age: 18Years +
All Genders
ID06828575

Evaluation of the Success of Artificial Intelligence Models in Interpreting Arterial Waveform Analysis Data

Led by Kanuni Sultan Suleyman Training and Research Hospital · Updated on 2025-03-04

145

Participants Needed

1

Research Sites

N/A

Total Duration

On this page

AI-Summary

What this Trial Is About

Researchers are evaluating the ability of artificial intelligence (AI) models, specifically ChatGPT-4 and Gemini 2.0, to interpret arterial waveform analysis data from adult patients undergoing elective surgery. The study aims to determine how accurately these AI models can detect hemodynamic abnormalities, how well their diagnostic suggestions match expert anesthesiologist assessments, and whether their treatment recommendations are clinically appropriate. This observational study focuses on improving decision-support tools in perioperative and critical care settings by enhancing the interpretation of complex hemodynamic data. Participants will undergo standard hemodynamic monitoring using the MostCare arterial waveform analysis device during elective surgery. Data collection will occur at multiple time points: before anesthesia induction, after intubation but before surgery, and during key surgical events requiring hemodynamic intervention. The anonymized waveform data will be analyzed by AI models to detect abnormalities, suggest diagnoses, and recommend treatments. Experienced anesthesiologists will independently review these AI-generated results to validate accuracy and relevance. Throughout the study, participants' hemodynamic data and AI analyses will be compared against expert assessments. Researchers will measure the accuracy of AI in detecting abnormalities, the agreement between AI and anesthesiologist diagnoses, and the clinical suitability of AI treatment suggestions. No additional interventions beyond routine care are involved. The study's duration is approximately six months, aiming to explore AI's potential to support clinical decision-making and improve patient safety during surgery.

CONDITIONS

Brief Title

Evaluation of the Success of Artificial Intelligence Models in Interpreting Arterial Waveform Analysis Data

Who Can Participate

Age: 18Years +
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Age 18 years or older
  • Undergoing elective surgery with arterial waveform monitoring as part of standard perioperative care
  • Hemodynamic data successfully recorded using the MostCare monitoring system
  • Able to provide informed consent to participate in the study
Not Eligible

You will not qualify if you...

  • Incomplete or corrupted hemodynamic data preventing reliable analysis
  • Emergency surgery cases
  • Severe arrhythmias or hemodynamic instability affecting arterial waveform interpretation
  • Refusal to participate or withdrawal of consent
  • Contraindications to arterial catheterization such as coagulopathy or severe peripheral vascular disease

AI-Screening

AI-Powered Screening

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Your Study Journey

Screening

Duration - 2 to 4 weeks

Participants are screened for eligibility to participate in the trial.

1 visit (in-person)

Monitoring

Duration - During the perioperative period (typically hours on the day of surgery)

Participants undergoing elective surgery are monitored using routine arterial waveform analysis during perioperative care. Data is collected at pre-anesthesia, post-anesthesia induction, and intraoperative periods to assess hemodynamic status.

Continuous monitoring during surgery with data collection at 3 key time points

Long-term Monitoring

Duration - Up to 1 day post data collection

Collected arterial waveform data is analyzed by AI models and validated by expert anesthesiologists to evaluate AI accuracy and clinical relevance.

No additional visits; analysis is performed remotely on collected data

Trial Site Locations

Total: 1 location

1

Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital

Istanbul, Turkey (Türkiye), 34303

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Research Team

E

Engin ihsan Turan, Specialist

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

0

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