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Akademický článek

Mobilization with cyclophosphamide reduces the number of lymphocyte subpopulations in the leukapheresis product and delays their reconstitution after autologous hematopoietic stem cell transplantation in patients with multiple myeloma

Autor: Skerget Matevz, Skopec Barbara, Zontar Darja, Cernelc Peter

Publikováno v: Radiology and Oncology, Vol 50, Iss 4, Pp 402-408 (2016)

Autologous hematopoietic stem cell transplantation is considered the standard of care for younger patients with multiple myeloma. Several mobilization regimens are currently used, most commonly growth factors alone or in combination with chemotherapy

Externí odkaz: https://doaj.org/article/c1856435059544f488ff27eddc51e3e2

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Differentiating Viral and Bacterial Infections: A Machine Learning Model Based on Routine Blood Test Values

Autor: Gunčar, Gregor, Kukar, Matjaž, Smole, Tim, Moškon, Sašo, Vovko, Tomaž, Podnar, Simon, Černelč, Peter, Brvar, Miran, Notar, Mateja, Köster, Manca, Jelenc, Marjeta Tušek, Notar, Marko

Publikováno v: Heliyon, Volume 10, ISSUE 8, e29372, Cell, April 30, 2024

The growing threat of antibiotic resistance necessitates accurate differentiation between bacterial and viral infections for proper antibiotic administration. In this study, a Virus vs. Bacteria machine learning model was developed to distinguish bet

Externí odkaz: http://arxiv.org/abs/2305.07877

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COVID-19 diagnosis by routine blood tests using machine learning

Autor: Kukar, Matjaž, Gunčar, Gregor, Vovko, Tomaž, Podnar, Simon, Černelč, Peter, Brvar, Miran, Zalaznik, Mateja, Notar, Mateja, Moškon, Sašo, Notar, Marko

Physicians taking care of patients with coronavirus disease (COVID-19) have described different changes in routine blood parameters. However, these changes, hinder them from performing COVID-19 diagnosis. We constructed a machine learning predictive

Externí odkaz: http://arxiv.org/abs/2006.03476

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Application of machine learning for hematological diagnosis

Autor: Gunčar, Gregor, Kukar, Matjaž, Notar, Mateja, Brvar, Miran, Černelč, Peter, Notar, Manca, Notar, Marko

Quick and accurate medical diagnosis is crucial for the successful treatment of a disease. Using machine learning algorithms, we have built two models to predict a hematologic disease, based on laboratory blood test results. In one predictive model,

Externí odkaz: http://arxiv.org/abs/1708.00253

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Akademický článek

Activated phosphoinositide 3-kinase δ syndrome associated with nephromegaly, growth hormone deficiency, bronchiectasis: a case report

Autor: Megan Craig, Bob Geng, Kristen Wigby, Susan A. Phillips, Christine Bakhoum, John Naheedy, Mateja Cernelc-Kohan

Publikováno v: Allergy, Asthma & Clinical Immunology, Vol 18, Iss 1, Pp 1-8 (2022)

Abstract Background Activated phosphoinositide 3-kinase (PI3K) δ syndrome (APDS) is a rare form of primary immunodeficiency with 243 known cases reported in the literature. Known findings associated with the condition include recurrent sinusitis and

Externí odkaz: https://doaj.org/article/c1b6e08dcffa482d8248acc1b9886c17

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Case report: Rare lung disease of infancy diagnosed with the assistance of a home pulse oximetry baby monitor

Autor: Kevin H. Yang, Art Kulatti, Kimberly Sherer, Aparna Rao, Mateja Cernelc-Kohan

Publikováno v: Frontiers in Pediatrics, Vol 10 (2022)

Neuroendocrine cell hyperplasia of infancy (NEHI) is a rare childhood interstitial lung disease characterized by a gradual onset of tachypnea, hypoxemia, and failure to thrive in the first 2 years of life. NEHI is challenging to diagnose and can masq

Externí odkaz: https://doaj.org/article/0bbdea5f186541f399bbfb2e63c43b55

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