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Predictive model of intrahepatic collateral vessels among hepatic veins in patients with liver tumors involving the caval confluence.

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January 2025

Department of Biomedical Sciences, Humanitas University, Milan, Italy; Department of Hepatobiliary & General Surgery, IRCCS Humanitas Research Hospital, Milan, Italy. Electronic address:

Background: Communicating vessels among hepatic veins in patients with tumors invading/compressing hepatic veins at their caval confluence facilitate new surgical solutions. Although their recognition by intraoperative ultrasound has been described, the possibility of preoperative detection still remains uncertain. We aimed to develop a model to predict their presence before surgery.

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Background: Segmentation models for clinical data experience severe performance degradation when trained on a single client from one domain and distributed to other clients from different domain. Federated Learning (FL) provides a solution by enabling multi-party collaborative learning without compromising the confidentiality of clients' private data.

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Traumatic injury remains a leading cause of death worldwide, with traumatic bleeding being one of its most critical and fatal consequences. The use of whole-body computed tomography (WBCT) in trauma management has rapidly expanded. However, interpreting WBCT images within the limited time available before treatment is particularly challenging for acute care physicians.

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Objective: Epilepsy is a common neurological disease affecting nearly 1% of the global population, and temporal lobe epilepsy (TLE) is the most common type. Patients experience recurrent seizures and chronic cognitive deficits that can impact their quality of life, ability to work, and independence. These cognitive deficits often extend beyond the temporal lobe and are not well understood.

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