• Mashup Score: 6

    [Pediatrics] Marina Golubeva; Elena Rakitina; Sergey Minaev; Igor Kirgizov; Alexandr Obedin; Mikhail Aksel’rov; Natusya Barova; Elena Aleksandrovna Bochnyuk; Our prospective nonrandomized controlled study enrolled 165 children with acute pneumonia (AP) from 2 to 18 years of age, which included 51 (30.9 %) children with ANP. There were 91 (55.2 %) boys and 73 (44.8 %) girls. Dynamic complex…

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    [Neurology] Stas Selitsky; Natalya Selitskaya; Joachim Schult; This paper analyzes the Machine Learning approach to classifying sleep electroencephalograms recorded from newborns at risk of brain pathologies. The newborns were in different age groups counted in weeks of post conceptional age. We consider solutions of the EEG task as a multiclass problem which can be resolved with Decision Tree…

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    • See also Machine learning approach to classification of sleep electroencephalograms from newborns at risk of brain pathologies #MedTwitterAI #botpenguin #chatbots #AI #healthbot #botmd #healthcareheroes #pandamic #sminaev #machinelearning #doctors https://t.co/OHLAAuCF1a https://t.co/e91KOT5vGQ

  • Mashup Score: 2

    Texture features are designed to quantitatively evaluate patterns of spatial distribution of image pixels for purposes of image analysis and interpretation. Unexplained variations in the texture patterns often lead to misinterpretation and undesirable consequences in medical image analysis. In this paper we explore the ability of machine learning (ML) methods to design a radiology test of…

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    • Deep learning for early detection of pathological changes in X-ray bone microstructures in patients with #osteoarthritis #DeepLearning #MedTwitterAI #botpenguin #chatbots #AI #healthbot #botmd #healthcareheroes #pandamic #usa #machinelearning #doctors https://t.co/TJf5VpV689 https://t.co/oCFDx31hxO