Publications by authors named "V Martinez Ibanez"

Purpose: To assess the diagnostic performance of hemoglobin concentration for Meckel's diverticulum (MD) and evaluate if hemoglobin levels could be useful in the surgical decision-making process of children with lower gastrointestinal bleeding (LGIB).

Methods: Retrospective cohort study of children with LGIB attending the emergency department between 2011 and 2021. Episodes of LGIB were divided into two groups: MeckD (MD diagnosed by surgery) and non-MeckD.

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In various applications, multiscale entropy (MSE) is often used as a feature to characterize the complexity of the signals in order to classify them. It consists of estimating the sample entropies (SEs) of the signal under study and its coarse-grained (CG) versions, where the CG process amounts to (1) filtering the signal with an average filter whose order is the scale and (2) decimating the filter output by a factor equal to the scale. In this paper, we propose to derive a new variant of the MSE.

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This concise review summarizes the literature on noncontingent reinforcement in the treatment of pediatric feeding disorder from 2018 to 2022. We reviewed 15 published behavior-analytic feeding studies to identify how often the term noncontingent reinforcement is used, what form of noncontingent reinforcement is delivered, and what the effects of noncontingent reinforcement are on behavior when it is included in treatment. Implications and directions for future research are discussed.

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Elevated levels of Fetal Hemoglobin interfere with polymerization of sickle hemoglobin thereby reducing anemia, lessening the severity of symptoms, and increasing life span of patients with sickle cell disease. An affordable, small molecule drug that stimulates HbF expression in vivo would be ideally suited to treat the large numbers of SCD patients that exist worldwide. Our previous work showed that administration of the LSD1 (KDM1A) inhibitor RN-1 to normal baboons increased Fetal Hemoglobin (HbF) and was tolerated over a prolonged treatment period.

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Human or time resources can sometimes fall short in medical image diagnostics, and analyzing images in full detail can be a challenging task. With recent advances in artificial intelligence, an increasing number of systems have been developed to assist clinicians in their work. In this study, the objective was to train a model that can distinguish between various fracture types on different levels of hierarchical taxonomy and detect them on 2D-image representations of volumetric postmortem computed tomography (PMCT) data.

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