Zobrazeno 1 - 10 of 101 pro vyhledávání: '"J, Prim"'
1
Akademický článek
A randomized controlled trial evaluating the efficacy of systemic ceftiofur administration for metritis therapy in dairy cows and the effect of metritis cure on economically important outcomes
Autor: P.R. Menta, L. Fernandes, J. Prim, E. De Oliveira, F. Lima, K.N. Galvão, N. Noyes, M.A. Ballou, V.S. Machado
Publikováno v: Journal of Dairy Science, Vol 107, Iss 9, Pp 7092-7105 (2024)
ABSTRACT: The main objective of this study was to evaluate the effect of ceftiofur on metritis cure, milk yield, reproductive performance, and culling up to 300 DIM. The secondary objective was to evaluate the effect of metritis cure at 5 (early cure
Externí odkaz: https://doaj.org/article/59209099c4cd4f40a9fca5d3d4e9d4ad
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2
Akademický článek
Predictive models for metritis cure using farm-collected data, metabolic and inflammation biomarkers, and hemogram variables measured at diagnosis
Autor: P.R. Menta, J. Prim, E. de Oliveira, F. Lima, K.N. Galvão, N. Noyes, M.A. Ballou, V.S. Machado
Publikováno v: Journal of Dairy Science, Vol 107, Iss 7, Pp 5016-5028 (2024)
ABSTRACT: Our objective was to evaluate the accuracy of predictive models for metritis spontaneous cure (SC) and cure among ceftiofur-treated cows using farm-collected data only, and with the addition of hemogram variables and circulating concentrati
Externí odkaz: https://doaj.org/article/335d075f31f745ea975e928bf4d9b168
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3
Effects of gonadal steroids on reward circuitry function and anhedonia in women with a history of postpartum depression
Autor: C E, Schiller, E, Walsh, T A, Eisenlohr-Moul, J, Prim, G S, Dichter, L, Schiff, J, Bizzell, S L, Slightom, E C, Richardson, A, Belger, P, Schmidt, D R, Rubinow
Publikováno v: Journal of Affective Disorders. 314:176-184
Reward system dysfunction is evident across neuropsychiatric conditions. Here we present data from a double-blinded pharmaco-fMRI study investigating the triggering of anhedonia and reward circuit activity in women.The hormonal states of pregnancy an
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::365ac058140d629b60021ee9c1be382f
https://doi.org/10.1016/j.jad.2022.06.078
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4
Akademický článek
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5
Akademický článek
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6
Akademický článek
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7
Predicting mortality in cardiovascular patients using electrocardiogram data and artificial intelligence
Autor: S Wegener, D Gruen, J Prim, N Gumpfer, J S Wolter, C W Hamm, C Liebetrau, J Hannig, M Guckert, T Keller
Publikováno v: European Heart Journal. 42
Background/Introduction The electrocardiogram (ECG) is an ubiquitously used non-invasive tool for diagnosis and risk prediction in cardiology, granting deep extensive insights into the heart. Artificial intelligence (AI) is a modern resource allowing
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e3841b1eb269f50dd8d116370d4fefa6
https://doi.org/10.1093/eurheartj/ehab724.1132
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8
On the importance of representative datasets in ECG-based artificial intelligence
Autor: N Gumpfer, S Wegener, J Prim, D Gruen, J Hannig, T Keller, M Guckert
Publikováno v: European Heart Journal. 42
Background/Introduction ECG-based artificial intelligence (AI) is an emerging field in digital cardiology. Training on diseased records vs. healthy controls is common practice. We aimed to evaluate if such an approach can lead to unwanted behaviour i
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::970cfe415363f3019897bd04e06f5759
https://doi.org/10.1093/eurheartj/ehab724.3060
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9
A data-pipeline processing electrocardiogram recordings for use in artificial intelligence algorithms
Autor: J Prim, T Uhlemann, N Gumpfer, D Gruen, S Wegener, S Krug, J Hannig, T Keller, M Guckert
Publikováno v: European Heart Journal. 42
Introduction Artificial intelligence (AI) can be used for various tasks in medicine and specifically in cardiology. Medical data such as electrocardiogram recordings (ECGs) are widely used and universally accepted as diagnostic and prognostic tools.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::64d52be89d101c595d2d85681aeb5e7c
https://doi.org/10.1093/eurheartj/ehab724.3041
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10
Detecting a broader spectrum of cardiac pathologies in electrocardiogram data by applying a deep neural network designed to detect a specific cardiac disease
Autor: S Wegener, T Schmidt, J Prim, N Gumpfer, D Gruen, J Hannig, M Guckert, T Keller
Publikováno v: European Heart Journal. 42
Background/Introduction The electrocardiogram (ECG) is a widely used and inexpensive tool that provides extensive insights into the cardiac structure and function. Artificial intelligence (AI) algorithms, especially deep learning (DL) models, are eff
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f256bffc2e5ed838d6ffe6a67c24efbb
https://doi.org/10.1093/eurheartj/ehab724.3063
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