Skip to main content

Table 2 Risk management plan for procedural and technical risks

From: Machine learning for the rElapse risk eValuation in acute biliary pancreatitis: The deep learning MINERVA study protocol

Risk

Proposed solution

Procedural risk: risks related to patient recruitment.

If the number of patients is not met by the 6th month of the project, the following centers will be contacted for the enrollment of additional patients:

1. General and Oncologic Surgery Unit, Santa Croce and Carle Hospital, Cuneo, Italy

2. Chirurgia Generale 2, ASST Spedali Civili di Brescia, Brescia, Italy

3. Policlinico Umberto I Sapienza University of Rome, Rome, Italy

Technical Risk: Difficulties and potential delays in the implementation of the algorithm.

Machine learning experts will be sought, who have already collaborated with the PI and local leads of the project such as:

• Institute of Cognitive Sciences and Technologies, National Research Council, CNR, Italy;

• Smarted srl, Italy. A start-up with years of expertise in national and international research projects in the field of ML;

• Prof. Barbara Webb, from the Institute for Perception, Action and Behaviour, School of Informatics, University of Edinburgh, United Kingdom

• ML experts Prof. Davide Marocco and Dr. Onofrio Gigliotta (Federico II University, Naples, Italy)