Bogdan Silviu Ungureanu, Dan Ionut Gheonea, Dan Nicolae Florescu, Sevastita Iordache, Sergiu Marian Cazacu, Vlad Florin Iovanescu, Ion Rogoveanu, Adina Turcu-Stiolica
BACKGROUND: Non-endoscopic risk scores, Glasgow Blatchford (GBS) and admission Rockall (Rock), are limited by poor specificity. The aim of this study was to develop an Artificial Neural Network (ANN) for the non-endoscopic triage of nonvariceal upper gastrointestinal bleeding (NVUGIB), with mortality as a primary outcome. METHODS: Four machine learning algorithms, namely, Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), logistic regression (LR), K-Nearest Neighbor (K-NN), were performed with GBS, Rock, Beylor Bleeding score (BBS), AIM65, and T-score...
2023: Frontiers in Medicine