4,634 research outputs found

    Jefferson Digital Commons quarterly report: January-March 2020

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    This quarterly report includes: New Look for the Jefferson Digital Commons Articles COVID-19 Working Papers Educational Materials From the Archives Grand Rounds and Lectures JeffMD Scholarly Inquiry Abstracts Journals and Newsletters Master of Public Health Capstones Oral Histories Posters and Conference Presentations What People are Saying About the Jefferson the Digital Common

    Application of Texture Descriptors to Facial Emotion Recognition in Infants

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    The recognition of facial emotions is an important issue in computer vision and artificial intelligence due to its important academic and commercial potential. If we focus on the health sector, the ability to detect and control patients’ emotions, mainly pain, is a fundamental objective within any medical service. Nowadays, the evaluation of pain in patients depends mainly on the continuous monitoring of the medical staff when the patient is unable to express verbally his/her experience of pain, as is the case of patients under sedation or babies. Therefore, it is necessary to provide alternative methods for its evaluation and detection. Facial expressions can be considered as a valid indicator of a person’s degree of pain. Consequently, this paper presents a monitoring system for babies that uses an automatic pain detection system by means of image analysis. This system could be accessed through wearable or mobile devices. To do this, this paper makes use of three different texture descriptors for pain detection: Local Binary Patterns, Local Ternary Patterns, and Radon Barcodes. These descriptors are used together with Support Vector Machines (SVM) for their classification. The experimental results show that the proposed features give a very promising classification accuracy of around 95% for the Infant COPE database, which proves the validity of the proposed method.This work has been partially supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) under project CloudDriver4Industry TIN2017-89266-R, and by the Conselleria de Educación, Investigación, Cultura y Deporte, of the Community of Valencia, Spain, within the program of support for research under project AICO/2017/134

    The Influence of the Method of Cerebral Protection During Neonatal Cardiac Surgery on The Development of Attention Deficit/Hyperactivity Disorder

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    Complex congenital heart disease is a common birth defect requiring surgery soon after birth. Surgery can use a complete interruption of cerebral blood flow (DHCA) or it can be performed using regional low flow perfusion (RLFP). Either approach places the neonate at risk for oxygen deprivation resulting in neurodevelopmental impairment and Attention Deficit/Hyperactivity Disorder (ADHD). RLFP has been widely adopted but its effect on ADHD has not been elucidated. We extracted surgical records data and surveyed parents of 5-16 year old children who had neonatal surgery using DHCA or RLFP in 1995-2006 to determine the prevalence of ADHD after DHCA vs. RLFP. ADHD was negatively associated with increased RLFP time (p \u3c .05) when controlling for DHCA time, and a primary diagnosis of interrupted aortic arch. This finding confirms that use of RLFP is associated with a reduced incidence of ADHD
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