AI-Based Real-Time Detection of Surgical Smoke Using Endoscopic Data

University Hospital Tuebingen30 enrolled

Overview

The goal of this observational, prospective monocentric pilot study is to generate a pilot dataset to train a computer-assisted model for automatic, intraoperative detection of surgical smoke gas. Women with indications for laparoscopic evaluation requiring the use of HF surgery (expecting the formation of smoke gas) and a smoke evacuation system (Karl Storz S-Pilot) are employed.

Detection of surgical smoke gas with an accuracy F1 score of \>= 0.8 on test datasets. The activation of the S-Pilot by clinic personnel will be used as the gold standard.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Detection of Surgical Smoke Gas Using AI

Eligibility

Sex: FEMALEMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * \- Age ≥ 18 years * Written consent after receiving information * Indication for surgical treatment using HF surgery Exclusion Criteria: * \- Expected lack of compliance by the patient or inability of the patient to understand the meaning and purpose of the clinical trial * Lack of patient consent * S-Pilot cannot be used

Locations (1)

Department of Women's Health, University Hospital

Tübingen, Germany

RECRUITING

Outcomes

Primary Outcomes

Detection of surgical smoke gas

Detection of surgical smoke gas with an accuracy of an F1 score of ≥ 0.8 on test data sets.

Time frame: At the end of the study (9 months)

Central Contacts

Prof. Dr. Bernhard Krämer

CONTACT

+497071 2982211 bernhard.kraemer@med.uni-tuebingen.de

Data from ClinicalTrials.gov

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