Articolul precedent |
Articolul urmator |
403 0 |
SM ISO690:2012 IAPĂSCURTĂ, Victor, BELÎI, Adrian. Preclinical Stage of Building a Machine Learning System for Sepsis Prediction: A Comparative Study of Four Algorithms. In: IFMBE Proceedings: . 5th International Conference on Nanotechnologies and Biomedical Engineering, Ed. 5, 3-5 noiembrie 2021, Chişinău. Chişinău: Pontos, 2022, Ediția 5, Vol.87, pp. 448-455. ISSN 16800737. DOI: https://doi.org/10.1007/978-3-030-92328-0_58 |
EXPORT metadate: Google Scholar Crossref CERIF DataCite Dublin Core |
IFMBE Proceedings Ediția 5, Vol.87, 2022 |
|||||||
Conferința "Conference on Nanotechnologies and Biomedical Engineering" 5, Chişinău, Moldova, 3-5 noiembrie 2021 | |||||||
|
|||||||
DOI:https://doi.org/10.1007/978-3-030-92328-0_58 | |||||||
Pag. 448-455 | |||||||
|
|||||||
Vezi articolul | |||||||
Rezumat | |||||||
From the point of view of data engineering, the application of machine learning methods in the case of data represented by multivariate multimodal time series is a difficult task, but with a possible practical potential, which is insufficiently explored. From a medical point of view, the conditions described by this type of data are current problems in medicine, especially in anesthesia and intensive care and particularly in case of sepsis. The early diagnosis of life-threatening conditions can lead to increased treatment success, reduced mortality and reduced cost of care for this group of patients, especially in complex cases. This paper describes a research focused on identifying the most appropriate machine learning algorithm to be used for further investigations. It presents some results concerning the preclinical stage in developing of a machine learning system for early sepsis prediction with an anticipated potential of improving the clinical management of patients with sepsis. |
|||||||
Cuvinte-cheie algorithmic complexity, machine learning, Machine Learning Algorithms, Sepsis management |
|||||||
|