Vascular injury during cholecystectomy: A multicenter critical analysis behind the drama.

Background: The management of a vascular injury during cholecystectomy is still very complicated, especially in centers not specialized in complex hepatobiliary surgery.

Methods: This was a multi-institutional retrospective study in patients with vascular injuries during cholecystectomy from 18 centers in 4 countries. The aim of the study was to analyze the management of vascular injuries focusing on referral, time to perform the repair, and different treatments options outcomes.

Machine Learning-Based Analysis in the Management of Iatrogenic Bile Duct Injury During Cholecystectomy: a Nationwide Multicenter Study.

Background: Iatrogenic bile duct injury (IBDI) is a challenging surgical complication. IBDI management can be guided by artificial intelligence models. Our study identified the factors associated with successful initial repair of IBDI and predicted the success of definitive repair based on patient risk levels.

An ultra-compact particle size analyser using a CMOS image sensor and machine learning.

Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost.

[Pediatric clinical experience in infectious endocarditis due to Candida spp].

Background: Treatment and outcome of Candida spp infectious endocarditis in children it most be based on treatment guidelines, however there are some controversies.

Aim: To describe our experience on treatment of pediatric candidal infective endocarditis.

Methods: Analytic prospective study, from January 2006 to December 2017.