Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Machine learning operations"'
Autor:
Zihan Li, Yibo Zhang, Zixiang Chen, Jiangming Chen, Hui Hou, Cheng Wang, Zheng Lu, Xiaoming Wang, Xiaoping Geng, Fubao Liu
Publikováno v:
Frontiers in Digital Health, Vol 6 (2024)
BackgroundMethods for accurately predicting the prognosis of patients with recurrent hepatolithiasis (RH) after biliary surgery are lacking. This study aimed to develop a model that dynamically predicts the risk of hepatolithiasis recurrence using a
Externí odkaz:
https://doaj.org/article/36a949bef1374b9ab97985deba2fe3a4
Autor:
Sotiris Pelekis, Theodosios Pountridis, Georgios Kormpakis, George Lampropoulos, Evangelos Karakolis, Spiros Mouzakitis, Dimitris Askounis
Publikováno v:
SoftwareX, Vol 27, Iss , Pp 101758- (2024)
This paper presents DeepTSF, a comprehensive machine learning operations (MLOps) framework aiming to innovate time series forecasting through workflow automation and codeless modeling. DeepTSF automates key aspects of the machine learning (ML) lifecy
Externí odkaz:
https://doaj.org/article/3e30721114234af18753cc60913a1392
Publikováno v:
Frontiers in Digital Health, Vol 6 (2024)
BackgroundDischarge date prediction plays a crucial role in healthcare management, enabling efficient resource allocation and patient care planning. Accurate estimation of the discharge date can optimize hospital operations and facilitate better pati
Externí odkaz:
https://doaj.org/article/973375a597954919ae87e80ab7f5b768
Publikováno v:
Computers, Vol 13, Iss 10, p 252 (2024)
Machine learning (ML) revolutionized traditional machine fault detection and identification (FDI), as complex-structured models with well-designed unsupervised learning strategies can detect abnormal patterns from abundant data, which significantly r
Externí odkaz:
https://doaj.org/article/fa04d4ef3bbd43a99e6eb8b24c7f538d
Publikováno v:
Internet Research, 2023, Vol. 33, Issue 7, pp. 168-205.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/INTR-10-2022-0769
Publikováno v:
Frontiers in Biomedical Technologies, Vol 11, Iss 3 (2024)
Purpose: In recent years, the use of Steady-State Visual Evoked Potentials (SSVEPs) in Brain-Computer Interface (BCI) systems has dramatically increased across several fields, such as rehabilitation, cognitive impairment, and brain disease or disorde
Externí odkaz:
https://doaj.org/article/48f53b794384416ab93b858dbe62d4cf
Autor:
Ryan C. Godwin, Ryan L. Melvin
Publikováno v:
SoftwareX, Vol 26, Iss , Pp 101723- (2024)
In the era of big data analytics and AI applications, data provenance is as important as ever, particularly as applications emerge in vital industries like healthcare. Additionally, as the suites of tools and packages grow exponentially, code transpa
Externí odkaz:
https://doaj.org/article/eb70722fa39540eb93bd956cf95255a9
Autor:
Taras Ustyianovych, Nadiia Kasianchuk, Halina Falfushynska, Solomiia Fedushko, Eduard Siemens
Publikováno v:
Proceedings of the International Conference on Applied Innovations in IT, Vol 11, Iss 2, Pp 81-90 (2023)
The availability of robust end-to-end ML processes plays a crucial role in delivering an accurate and reliable system for real-time text data inference. In this paper, we present an approach to building machine learning operations (MLOps) and an obse
Externí odkaz:
https://doaj.org/article/70543692246b4de99cb32cbf020334a5
Autor:
Bilal Mirza, Xinyang Li, Kris Lauwers, Bhargava Reddy, Anja Muller, Craig Wozniak, Sina Djali
Publikováno v:
Healthcare Analytics, Vol 3, Iss , Pp 100159- (2023)
In clinical trial monitoring, substantial resources are allocated to perform source data verification (SDV). SDV ensures accurate and reliable transcription of trial participant information. Clinical site visits are typically scheduled at a fixed fre
Externí odkaz:
https://doaj.org/article/ce6457d4fa954964a8b9eb444ce50f60
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