artificial neural networks in the outcome prediction of adjustable gastric banding in obese women人工神经网络的预测结果在肥胖女性的可调节胃扎带手术.pdf

Artificial Neural Networks in the Outcome Prediction of Adjustable Gastric Banding in Obese Women 1 2 2 3 2 4 Paolo Piaggi *, Chita Lippi , Paola Fierabracci , Margherita Maffei , Alba Calderone , Mauro Mauri , 2 4 2 2 1 Marco Anselmino , Giovanni Battista Cassano , Paolo Vitti , Aldo Pinchera , Alberto Landi , Ferruccio Santini2 1 Department of Electrical Systems and Automation, University of Pisa, Pisa, Italy, 2 Department of Endocrinology and Metabolism, University Hospital of Pisa, Pisa, Italy, 3 Dulbecco Telethon Institute at Department of Endocrinology and Metabolism, University Hospital of Pisa, Pisa, Italy, 4 Department of Psychiatry, Neurobiology, Pharmacology and Biotechnology, School of Medicine, University of Pisa, Pisa, Italy Abstract Background: Obesity is unanimously regarded as a global epidemic and a major contributing factor to the development of many common illnesses. Laparoscopic Adjustable Gastric Banding (LAGB) is one of the most popular surgical approaches worldwide. Yet, substantial variability in the results and significant rate of failure can be expected, and it is still debated which categories of patients are better suited to this type of bariatric procedure. The aim of this study was to build a statistical model based on both psychological and physical data to predict weight loss in obese patients treated by LAGB, and to provide a valuable instrument for the selection of patients that may benefit from this procedure. Methodology/Principal Findings: The study population consisted of 172 obese women, with a mean 6SD presurgical and postsurgical Bod