The use of time lapse systems (TLS) in In Vitro Fertilization (IVF) labs to record developing embryos has paved the way for deep-learning based computer vision algorithms to assist embryologists in their morphokinetic evaluation. Today, most of the literature has characterized algorithms that predict pregnancy, ploidy or blastocyst quality, leaving to the side the task of identifying key morphokinetic events. Using a dataset of N = 1909 embryos collected from multiple clinics equipped with EMBRYOSCOPE/EMBRYOSCOPE+ (Vitrolife), GERI (Genea Biomedx) or MIRI (Esco Medical), this study proposes a novel deep-learning architecture to automatically detect 11 kinetic events (from 1-cell to blastocyst).
View Article and Find Full Text PDFWe report on the realization of an all-fiber laser source that delivers single-frequency pulses at 1645 nm, on a linearly polarized single-mode beam, based on stimulated Raman scattering in passive fibers. The pulse energy reaches 14 µJ for a repetition rate of 20 kHz, and the spectral linewidth is 9.5 MHz for 100 ns square pulses.
View Article and Find Full Text PDFObjective: To describe pain assessment, the pattern of analgesic and sedative drug use, and adverse drug reactions in a neonatal intensive care unit (NICU) during the postsurgery phase.
Method: Demographic characteristics, pain scores, and drug use were extracted and analyzed from electronic patient medical files for infants after surgery, admitted consecutively between January 2012 and June 2013.
Result: One hundred and sixty-eight infants were included.
Treatment initiation rates following fragility fractures have often been reported to be low and in recent years numerous programs have been implemented worldwide to increase them. This study aimed at describing osteoporosis (OP) treatment initiation in a representative sample of women who were hospitalized for a distal forearm fracture (DFF) or proximal humerus fracture (PHF) in 2009-2011 in France. The data source was a nationwide sample of 600,000 individuals, extracted from the French National Insurance Healthcare System database.
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