Fuzzy Classification of Bariatric Post-surgery Effectiveness

被引:0
|
作者
Arevalo, Aldo [1 ]
Pacheco, Ricardo [1 ]
Salgado, Catia M. [1 ]
van Loon, Saskia [2 ,3 ]
Boer, Arjen-Kars [2 ]
Vieira, Susana M. [1 ]
Kaymak, Uzay [3 ]
Sousa, Joao M. C. [1 ]
机构
[1] Univ Lisbon, Inst Super Tecn, IDMEC, Av Rovisco Pais, Lisbon, Portugal
[2] Catharina Hosp, Clin Chem, Michelangelolaan 2, NL-5623 EJ Eindhoven, Netherlands
[3] Eindhoven Univ Technol, Ind Engn & Innovat Sci, POB 513, NL-5600 MB Eindhoven, Netherlands
关键词
Fuzzy modeling; Bariatrics; total weight loss; Obesity; LONGITUDINAL DATABASE BOLD; EXCESS WEIGHT-LOSS; PREDICTION; SELECTION; AGE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The expected post-operatory weight loss is not always achieved after bariatric surgery. Efforts have been done to describe the causes. Recently, total weight loss (%TWL) has been pointed out to better assess weight loss in bariatric patients. However, there is no cut off point that delimits the patients who successfully achieve their weight goals after a bariatric surgery. In this work, a method based on fuzzy modeling is implemented to help clinicians setting up the best cut-off point in %TWL for a specific population. The best boundary to delimit success and failure will be selected based on the predictive performance of the assessed cut-off points: 25, 30, 35 and 40%TWL after one and two years of surgery. Area under the receiver operating characteristic curve (AUC) values of 0.70 and 0.75 were achieved for the first and second post-surgery periods, respectively. Further, features not previously described as predictors of weight loss were identified as good predictors of the outcome.
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页数:8
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