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1.
J Forensic Sci ; 62(2): 468-472, 2017 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-27907231

RESUMEN

Fetal deaths are important cases for forensic medicine, as well as for criminal and civil law. From a legal perspective, the determination of whether a deceased infant was stillborn is a difficult process. Such a determination is generally made during autopsy; however, no standardized procedures for this determination exist. Therefore, new facilitative approaches are needed. In this study, three new support systems based on 10 autopsy parameters were tested for their ability to correctly determine whether deceased infants were alive or stillborn. Performances were analyzed and compared with one another. The artificial neural networks and radial basis function network models had 90% accuracy (the highest among the models tested), 100% sensitivity, and 83.3% specificity. Thus, the models presented here provide additional insights for future studies concerning infant autopsies.


Asunto(s)
Técnicas de Apoyo para la Decisión , Nacimiento Vivo , Mortinato , Líquido Amniótico , Autopsia , Femenino , Humanos , Recién Nacido , Modelos Logísticos , Redes Neurales de la Computación , Embarazo , Alveolos Pulmonares/patología , Aspiración Respiratoria/patología , Sensibilidad y Especificidad
2.
Neuroreport ; 18(13): 1371-4, 2007 Aug 27.
Artículo en Inglés | MEDLINE | ID: mdl-17762715

RESUMEN

Cortical neurons in-vivo operate in a continuum of overall conductance states, depending on the average level of background synaptic input throughout the dendritic tree. We compare how variability, or fluctuations, in this input affects the statistics of the resulting 'spontaneous' or 'background' firing activity, between two extremes of the mean input corresponding to a low-conductance (LC) and a high-conductance (HC) state. In the HC state, we show that both firing rate and regularity increase with increasing variability. In the LC state, firing rate also increases with input variability, but in contrast to the HC state, firing regularity first decreases and then increases with an increase in the variability. At high levels of input variability, firing regularity in both states converge to similar values.


Asunto(s)
Potenciales de Acción/fisiología , Corteza Cerebral/citología , Modelos Neurológicos , Conducción Nerviosa/fisiología , Neuronas/fisiología , Sinapsis/fisiología , Animales , Inhibición Neural/fisiología , Ruido
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