Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Xianlong, Zeng"'
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
Abstract The adoption of electronic health records (EHR) has become universal during the past decade, which has afforded in-depth data-based research. By learning from the large amount of healthcare data, various data-driven models have been built to
Externí odkaz:
https://doaj.org/article/eb5992daee554040a6b03f52f5dee5d4
Publikováno v:
IEEE Open Journal of the Computer Society, Vol 2, Pp 62-71 (2021)
Accurately predicting patient expenditure in healthcare is an important task with many applications such as provider profiling, accountable care management, and capitated medical payment adjustment. Existing approaches mainly rely on manually designe
Externí odkaz:
https://doaj.org/article/90623c851deb4157a434793e20ea68b9
Autor:
Martin Kanovský, Júlia Halamová, Nicola Petrocchi, Helena Moreira, Eunjoo Yang, Jan Benda, Michael Barnett, Elmar Brähler, Xianlong Zeng, Markus Zenger
Publikováno v:
Mediterranean Journal of Clinical Psychology, Vol 9, Iss 1 (2021)
The purpose of this study was to examine the measurement invariance of the Self-Compassion Scale by IRT differential test functioning in ten distinct populations (n = 13623 participants) from ten different countries: Australia (n = 517), China (n = 3
Externí odkaz:
https://doaj.org/article/b18769b1050144059a9af9e223cd3d0e
Publikováno v:
Frontiers in Public Health, Vol 8 (2021)
Background: Early childhood dental care (ECDC) is a significant public health opportunity since dental caries is largely preventable and a prime target for reducing healthcare expenditures. This study aims to discover underlying patterns in ECDC util
Externí odkaz:
https://doaj.org/article/cb216981647d43ba83a86561b703f371
Publikováno v:
IEEE Open Journal of the Computer Society, Vol 2, Pp 62-71 (2021)
Accurately predicting patient expenditure in healthcare is an important task with many applications such as provider profiling, accountable care management, and capitated medical payment adjustment. Existing approaches mainly rely on manually designe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::682cc7e7b774a986c0fb4aa0cf4bd9dc
https://ieeexplore.ieee.org/document/9328319/
https://ieeexplore.ieee.org/document/9328319/
Publikováno v:
Scientific reports. 12(1)
The adoption of electronic health records (EHR) has become universal during the past decade, which has afforded in-depth data-based research. By learning from the large amount of healthcare data, various data-driven models have been built to predict
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dbe8d14c7128602dc8c0511dc8a9063
https://pubmed.ncbi.nlm.nih.gov/35256645
https://pubmed.ncbi.nlm.nih.gov/35256645
Publikováno v:
BCB
The claims data, containing medical codes, services information, and incurred expenditure, can be a good resource for estimating an individual's health condition and medical risk level. In this study, we developed Transformer-based Multimodal AutoEnc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47f0be4799bb096e93fd23a02d3eded6
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030840594
CD-MAKE
CD-MAKE
The black-box nature of machine learning models limits their use in case-critical applications, raising faithful and ethical concerns that lead to trust crises. One possible way to mitigate this issue is to understand how a (mispredicted) decision is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6d0fc40bd099209e3790fce56fff1a8
https://doi.org/10.1007/978-3-030-84060-0_20
https://doi.org/10.1007/978-3-030-84060-0_20
Publikováno v:
Frontiers in Public Health
Frontiers in Public Health, Vol 8 (2021)
Frontiers in Public Health, Vol 8 (2021)
Background: Early childhood dental care (ECDC) is a significant public health opportunity since dental caries is largely preventable and a prime target for reducing healthcare expenditures. This study aims to discover underlying patterns in ECDC util
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8850015d315b646c3f81b9ea61f57a2f
https://pubmed.ncbi.nlm.nih.gov/33537275
https://pubmed.ncbi.nlm.nih.gov/33537275
Publikováno v:
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 25
Various deep learning models have been developed for different healthcare predictive tasks using Electronic Health Records and have shown promising performance. In these models, medical codes are often aggregated into visit representation without con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::6adc1e395afceeb3cf1287996d793c3c
https://pubmed.ncbi.nlm.nih.gov/31797591
https://pubmed.ncbi.nlm.nih.gov/31797591