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  • Open Access

    CASE REPORT

    Stubborn Hypoxia in Neonates with D-Transposition of the Great Arteries after Arterial Switch Operation: Central Sleep Apnea as the Cause and Potential Indicator of Brain Immaturity

    Camden L. Hebson1,*, Kyle Bliton2, Amr Y. Hammouda1, Kaitlyn Barr3, W. Hampton Gray4, Mohini Gunnett2, Waldemar F. Carlo1

    Congenital Heart Disease, Vol.19, No.2, pp. 185-195, 2024, DOI:10.32604/chd.2024.048871 - 16 May 2024

    Abstract D-transposition of the great arteries (d-TGA) is surgically repaired with the arterial switch operation (ASO) with excellent results, however short and long-term morbidities still develop including neurocognitive delay. Clinically significant central sleep apnea is uncommon in non-premature infants, but when present indicates immature autonomic control of respiration likely due to a neurologic disorder. We report the unanticipated finding of central sleep apnea in four-term neonates with d-TGA after uncomplicated ASO, with the short-term complication of delayed hospital discharge and long-term concerns regarding this early marker of brain immaturity and its hindrance to normal development. Within More >

  • Open Access

    ARTICLE

    Neural Cryptography with Fog Computing Network for Health Monitoring Using IoMT

    G. Ravikumar1, K. Venkatachalam2, Mohammed A. AlZain3, Mehedi Masud4, Mohamed Abouhawwash5,6,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 945-959, 2023, DOI:10.32604/csse.2023.024605 - 01 June 2022

    Abstract Sleep apnea syndrome (SAS) is a breathing disorder while a person is asleep. The traditional method for examining SAS is Polysomnography (PSG). The standard procedure of PSG requires complete overnight observation in a laboratory. PSG typically provides accurate results, but it is expensive and time consuming. However, for people with Sleep apnea (SA), available beds and laboratories are limited. Resultantly, it may produce inaccurate diagnosis. Thus, this paper proposes the Internet of Medical Things (IoMT) framework with a machine learning concept of fully connected neural network (FCNN) with k-nearest neighbor (k-NN) classifier. This paper describes More >

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