Applying machine learning to primate bioacoustics: Review and perspectives.

This paper provides a comprehensive review of the use of computational bioacoustics as well as signal and speech processing techniques in the analysis of primate vocal communication. We explore the potential implications of machine learning and deep learning methods, from the use of simple supervised algorithms to more recent self-supervised models, for processing and analyzing large data sets obtained within the emergence of passive acoustic monitoring approaches. In addition, we discuss the importance of automated primate vocalization analysis in tackling essential questions on animal communication and highlighting the role of comparative linguistics in bioacoustic research.

Potentially Inappropriate Medication Dispensing in Outpatients: Comparison of Different Measurement Approaches.

Purpose Of The Research: This paper aims at comparing different approaches to measure potentially inappropriate medication (PIM) with routinely collected data on prescriptions, patient age institutionalization status (ie in nursing home or in the community). A secondary objective is to measure the rate and prevalence of PIM dispensing and to identify problematic practices in Switzerland.

Material And Methods: The studied population includes about 90,000 insured over 17 years old from a Swiss health maintenance organization in 2019 and 2020.

Detection of regularities in a random environment.

Regularity detection, or statistical learning, is regarded as a fundamental component of our cognitive system. To test the ability of human participants to detect regularity in a more ecological situation (i.e.

Nosocomial bacteremia: clinical significance of a single blood culture positive for coagulase-negative staphylococci.

Objectives: To describe the epidemiology of nosocomial coagulase-negative staphylococci (CoNS) bacteremia and to evaluate the clinical significance of a single blood culture positive for CoNS.

Design: A 3-year retrospective cohort study based on data prospectively collected through hospital-wide surveillance. Bacteremia was defined according to CDC criteria, except that a single blood culture growing CoNS was not systematically considered as a contaminant.