Can The Matrix Help Treat Recurrent Hepatocellular Carcinoma?
Menée à partir des données d'un registre italien portant sur 701 patients atteints d'un carcinome hépatocellulaire ayant récidivé après un premier traitement chirurgical (âge : 71 ans ; 21,5 % de femmes), cette étude évalue la performance d'un algorithme d'apprentissage automatique pour prédire la survie et éclairer la décision thérapeutique
In this issue of JAMA Surgery, Famularo et al created a model for determining optimal treatment after postoperative recurrence of hepatocellular carcinoma (HCC) using data from 30 Italian centers, along with validation using international multicenter databases. We congratulate Famularo et al for their meticulous analysis and robust results.This research represents an innovative application of artificial intelligence (AI) in the field of surgery. AI has 4 main aspects: (1) machine learning, (2) natural language processing, (3) artificial neural networks, and (4) computer vision. In their study, the authors used “supervised learning,” a part of machine learning, to create an accurate algorithm for predicting prognosis of HCC recurrence after an initial surgical approach. They also created an intuitive web application that may help allocate patients to the best potential treatment for their specific clinical characteristics.
JAMA Surgery , éditorial, 2021