Therapeutic Assistance and Decision-making Algorithms in Hepatobiliary Tumor Boards

Evaluation of the Trustworthiness of the Application of Artificial Intelligence and Decision Support Systems for the Creation of Tumor Conference Protocols

The goal of this observational study is to compare the recommendations of the artificial intelligence clinical decision support system 'ADBoard', with the recommendations of physicians by tumor conferences in patients with hepatobiliary tumors. The main questions it aims to answer are:

Can ADBoard achieve a high level of similar recommendations as physicians' tumor conferences? Can ADBoard consider a more complete set of patient-related data than in physicians' tumor conferences? Can ADBoard reduce the time between the first time the patient is discussed at the tumor conference and the start of the recommended treatment plan? Participants will have their hepatobiliary tumor treatments determined by either tumor conference with ADBoard, or tumor conference without ADBoard.

Inclusion Criteria:

• Age ≥ 18 years
• Valid informed consent
• Patient information available in the hospital information system or Health Data Platform (HDP)
• Enrollment in the hepatobiliary tumor conference
• Diagnosis of any of the following entities: Colorectal liver metastasis, Gallbladder carcinoma, Hepatocellular carcinoma (HCC), mixed cell carcinoma, or fibrolamellar carcinoma, Perihilar cholangiocarcinoma (Klatskin tumors), Intrahepatic cholangiocarcinoma (iCC)

Exclusion Criteria:

• Patient does not consent / incapable of giving consent
• Missing findings in the hospital information system
• Patient is seeking for a second opinion and is not being treated at the study institution