Utilité clinique des ultrasons osseux quantitatifs dans le dépistage de l'ostéoporose [Clinical utility of quantitative bone ultrasonography in the staging of osteoporosis]

Osteoporosis is well recognized as a public health problem in industrialized countries. Because of the efficiency of new treatments to decrease fracture risk, it is of a major interest to detect the patients who should benefit from such treatments. A diagnosis of osteoporosis is necessary before to start a specific treatment. This diagnosis is based on the measurement of the skeleton (hip and spine) with dual X-ray absorptiometry, using diagnostic criteria established by the World Health Organisation (WHO). In Switzerland, indications for bone densitometry are limited to precise situations. This technique cannot be applied for screening. For this purpose, peripheral measurements and particularly quantitative ultrasounds of bone seem to be promising. Indeed, several prospective studies clearly showed their predictive power for hip fracture risk in women aged more than 65 years. In order to facilitate the clinical use of bone ultrasounds, thresholds of risk of fracture and osteoporosis of the hip will be shortly published. This will integrate bone ultrasound in a global concept including bone densitometry and its indications, but also other risk factors for osteoporosis recognized by the Swiss association against osteoporosis (ASCO).

Les proches dans le Code civil

Le législateur du Code civil a introduit le terme « proche » dans de nombreuses dispositions, mais n'en propose aucune définition, ce qui laisse une grande marge de manoeuvre pour son interprétation et son application. La signification et la portée du terme ne seront ainsi pas les mêmes selon le domaine juridique et la situation de fait analysés. Face à cette grande diversité d'usage du terme, l'auteure de la contribution propose de l'appréhender selon les domaines et les buts dans lesquels il est utilisé par le législateur afin de réussir à tracer les contours des différents cercles de proches envisageables.

Intégration de méthodes de data mining dans le renseignement criminel : analyse par des structures issues de la théorie des graphes dans le profilage des stupéfiants

Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.