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- Saux, Patrick, et al.
(författare)
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Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study.
- 2023
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Ingår i: The Lancet. Digital health. - 2589-7500. ; 5:10
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Tidskriftsartikel (refereegranskat)abstract
- Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery.In this multinational retrospective observational study we enrolled adult participants (aged ≥18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year follow-up after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI.10231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30602 patient-years. Among participants in all 12 cohorts, 7701 (75·3%) were female, 2530 (24·7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2·8 kg/m2 (95% CI 2·6-3·0) and mean RMSE BMI was 4·7 kg/m2 (4·4-5·0), and the mean difference between predicted and observed BMI was -0·3 kg/m2 (SD 4·7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery.We developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions.SOPHIA Innovative Medicines Initiative 2 Joint Undertaking, supported by the EU's Horizon 2020 research and innovation programme, the European Federation of Pharmaceutical Industries and Associations, Type 1 Diabetes Exchange, and the Juvenile Diabetes Research Foundation and Obesity Action Coalition; Métropole Européenne de Lille; Agence Nationale de la Recherche; Institut national de recherche en sciences et technologies du numérique through the Artificial Intelligence chair Apprenf; Université de Lille Nord Europe's I-SITE EXPAND as part of the Bandits For Health project; Laboratoire d'excellence European Genomic Institute for Diabetes; Soutien aux Travaux Interdisciplinaires, Multi-établissements et Exploratoires programme by Conseil Régional Hauts-de-France (volet partenarial phase 2, project PERSO-SURG).
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| 2. |
- Tarrío, Diego, et al.
(författare)
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Neutron-induced fission cross sections of Th-232 and U-233 up to 1 GeV using parallel plate avalanche counters at the CERN n_TOF facility
- 2023
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Ingår i: Physical Review C. - : American Physical Society. - 2469-9985 .- 2469-9993. ; 107:4
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Tidskriftsartikel (refereegranskat)abstract
- The neutron-induced fission cross sections of Th-232 and U-233 were measured relative to U-235 in a wide neutron energy range up to 1 GeV (and from fission threshold in the case of Th-232, and from 0.7 eV in case of U-233), using the white-spectrum neutron source at the CERN Neutron Time-of-Flight (n_TOF) facility. Parallel plate avalanche counters (PPACs) were used, installed at the Experimental Area 1 (EAR1), which is located at 185 m from the neutron spallation target. The anisotropic emission of fission fragments were taken into account in the detection efficiency by using, in the case of U-233, previous results available in EXFOR, whereas in the case of Th-232 these data were obtained from our measurement, using PPACs and targets tilted 45 degrees with respect to the neutron beam direction. Finally, the obtained results are compared with past measurements and major evaluated nuclear data libraries. Calculations using the high-energy reaction models INCL++ and ABLA07 were performed and some of their parameters were modified to reproduce the experimental results. At high energies, where no other neutron data exist, our results are compared with experimental data on proton-induced fission. Moreover, the dependence of the fission cross section at 1 GeV with the fissility parameter of the target nucleus is studied by combining those ( p, f) data with our (n, f) data on Th-232 and U-233 and on other isotopes studied earlier at n_TOF using the same experimental setup.
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