Zobrazeno 1 - 10
of 1 855
pro vyhledávání: '"biomedical data"'
Autor:
H. A. Hristov, F. I. Batalov
Publikováno v:
Автоматизация технологических и бизнес-процессов, Vol 16, Iss 3, Pp 100-108 (2024)
Abstract.. Demographic change, such as the rapidly aging populations in many industrialized countries, along with the rise in chronic diseases (such as diabetes and heart disease), has prompted many professionals to explore how technology can allevia
Externí odkaz:
https://doaj.org/article/e9f44699728644a187928eb56a627c18
Publikováno v:
Jurnal Saintekom, Vol 14, Iss 2, Pp 195-207 (2024)
This study aims to evaluate the effectiveness and efficiency of various deep learning models in recognizing patterns within diverse biomedical datasets. The methods involved the collection of biomedical data from various public and synthetic sources,
Externí odkaz:
https://doaj.org/article/ff2140175c7540d182f97643b8cb4589
Autor:
Ahmad Al Badawi, Mohd Faizal Bin Yusof
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-25 (2024)
Abstract Purpose The objective of this research is to explore the applicability of machine learning and fully homomorphic encryption (FHE) in the private pathological assessment, with a focus on the inference phase of support vector machines (SVM) fo
Externí odkaz:
https://doaj.org/article/b999b8ebfc9b4b66852b57f1c358f840
Publikováno v:
BioMedInformatics, Vol 4, Iss 3, Pp 1672-1691 (2024)
Background: Biomedical data are usually collections of longitudinal data assessed at certain points in time. Clinical observations assess the presences and severity of symptoms, which are the basis for the description and modeling of disease progress
Externí odkaz:
https://doaj.org/article/00c1a7a5dc3f44c6bcff8e12d1de9b8d
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Effectiveness in health care is a specific characteristic of each intervention and outcome evaluated. Especially with regard to surgical interventions, organization, structure and processes play a key role in determining this parameter. In a
Externí odkaz:
https://doaj.org/article/3bd3c86671a54cbd9baef0a429a20b74
Publikováno v:
Frontiers in Physiology, Vol 15 (2024)
Predictive modeling of clinical time series data is challenging due to various factors. One such difficulty is the existence of missing values, which leads to irregular data. Another challenge is capturing correlations across multiple dimensions in o
Externí odkaz:
https://doaj.org/article/469956f3adec4ea6964d30b8acbf16a3
Autor:
Siddartha Pullakhandam, Susan McRoy
Publikováno v:
BioMedInformatics, Vol 4, Iss 1, Pp 661-672 (2024)
Background: Currently, discriminating Iron Deficiency Anemia (IDA) from other anemia requires an expensive test (serum ferritin). Complete Blood Count (CBC) tests are less costly and more widely available. Machine learning models have not yet been ap
Externí odkaz:
https://doaj.org/article/eee0d403d8244e8f80305468d809452b
Autor:
Parisa Movahedi, Valtteri Nieminen, Ileana Montoya Perez, Hiba Daafane, Dishant Sukhwal, Tapio Pahikkala, Antti Airola
Publikováno v:
IEEE Access, Vol 12, Pp 118637-118648 (2024)
Differentially private (DP) synthetic data has emerged as a potential solution for sharing sensitive individual-level biomedical data. DP generative models offer a promising approach for generating realistic synthetic data that aims to maintain the o
Externí odkaz:
https://doaj.org/article/d9c3a0691312462997bff20bffd13791
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-19 (2024)
Abstract Graph embedding techniques are using deep learning algorithms in data analysis to solve problems of such as node classification, link prediction, community detection, and visualization. Although typically used in the context of guessing frie
Externí odkaz:
https://doaj.org/article/0ac19e335e13460d9155682727e86283
Autor:
Alfred Ultsch, Jörg Hoffmann, Maximilian A. Röhnert, Malte von Bonin, Uta Oelschlägel, Cornelia Brendel, Michael C. Thrun
Publikováno v:
BioMedInformatics, Vol 4, Iss 1, Pp 197-218 (2024)
Typical state-of-the-art flow cytometry data samples typically consist of measures of 10 to 30 features of more than 100,000 cell “events”. Artificial intelligence (AI) systems are able to diagnose such data with almost the same accuracy as human
Externí odkaz:
https://doaj.org/article/ad9a48e9309b4116a54214ceb77b1f04