Zobrazeno 1 - 5
of 5
pro vyhledávání: '"David, Harary"'
Autor:
Sandra E. Reznik, Ayodele J. Akinyemi, David Harary, Mariam S. Latuga, Mamta Fuloria, Maureen J. Charron
Publikováno v:
BMC Pediatrics, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Background Neonatal and early-life gut microbiome changes are associated with altered cardiometabolic and immune development. In this study, we explored Cesarean delivery effects on the gut microbiome in our high-risk, under-resourced Bronx,
Externí odkaz:
https://doaj.org/article/f0de773dd4a54c3f9b1fc76d2601fcd7
Autor:
Mana Mann, David Harary, Shirley Louis, Tao Wang, Karen Bonuck, Carmen R. Isasi, Maureen J. Charron, Mamta Fuloria
Publikováno v:
Frontiers in Pediatrics, Vol 11 (2023)
Externí odkaz:
https://doaj.org/article/2069b91e902642cd8314c08ddb87c420
Autor:
Mana Mann, David Harary, Shirley Louis, Tao Wang, Karen Bonuck, Carmen R. Isasi, Maureen J. Charron, Mamta Fuloria
Publikováno v:
Frontiers in Pediatrics, Vol 11 (2023)
IntroductionThe effects of psychological distress/resilience on parent-child engagement (e.g., family dinners, reading) during the COVID-19 pandemic have not been well studied. Among very young children from underrepresented backgrounds enrolled in t
Externí odkaz:
https://doaj.org/article/2e7586d0865549dca47bdcf3d51a5155
Publikováno v:
Neoreviews
Epidemiologic studies have shown an association between an adverse intrauterine environment (eg, exposure to malnutrition) and an increased risk of developing cardiometabolic disease in adulthood. These studies laid the foundation for the development
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a46900353952ee89e129507829066c3c
https://doi.org/10.1542/neo.23-6-e363
https://doi.org/10.1542/neo.23-6-e363
Autor:
Alexandre Barachant, Victor He, David Harary, Silverio Joseph Bumanlag, John D. Long, David Putrino, K. Zoe Tsagaris, Behdad Dehbandi
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. 21:1386-1392
The objective of this study was to assess whether the novel application of a machine learning approach to data collected from the Microsoft Kinect 2 (MK2) could be used to classify differing levels of upper limb impairment. Twenty-four healthy subjec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::084c141d2263afd3aab5d3374912ea83
https://doi.org/10.1109/jbhi.2016.2606240
https://doi.org/10.1109/jbhi.2016.2606240