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Traditional classification algorithms consider learning problems that contain only one label, i.e., each example is associated with one single nominal target variable characterizing its property. However, the number of practical applications involving data with multiple target variables has increased. To learn from this sort of data, multi-label classification algorithms should be used. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem into several single-label classification problems. In this work, two well known methods based on this approach are used, as well as a third method we propose to overcome some deficiencies of one of them, in a case study using textual data related to medical findings, which were structured using the bag-of-words approach. The experimental study using these three methods shows an improvement on the results obtained by our proposed multi-label classification method.

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Introduction2-D ultrasound shear wave elastography (SWE) could be considered as a new noninvasive tool for monitoring fetal lung development based on evaluation of mechanical properties during pregnancy. Interesting results are available concerning the use of SWE on developing organs, especially on premature infants and animal models. The main objective in this study is to evaluate the feasibility of 2-D SWE in human fetal lungs between 24 and 34 weeks of gestation (WG). The secondary objective is to modellise fetal lung-to-liver elastography ratio (LLE ratio) and to assess variations between normal lung and lung surfactant-enriched after a corticosteroids course indicated for a threatened preterm labour (TPL).Methods/designA prospective case-control study will be performed between 24 and 34 WG. Fetal lungs and liver will be explored by SWE into two groups: fetuses of women with an uncomplicated pregnancy (control group) and fetuses of women with a TPL requiring administration of corticosteroids (cases group). LLE ratio will be defined as the value of the lung elasticity divided by the value of the liver elasticity.Primary judgement criterion is the value of elasticity modulus expressed in kilopascal. Lungs and liver will be explored through three measurements to define the most reproducible regions with the lowest intra- and inter-observer variability. Feasibility will be evaluated by assessing the number of examinations performed and the number of examinations with interpretable results. Intra- and inter-observer reproducibility will be evaluated by means of the intra-class correlation coefficient.Ethics and disseminationApproval of the study protocol was obtained from the human ethical research committee (Comité de Protection des Personnes EST II, process number 15/494) and the French National Agency for Medicines and Health Products Safety (process number 2015-A01575-44). All participants will sign a statement of informed consent.Trial registration numberNCT02870608; Recruiting.