Výsledky vyhledávání - "Rademakers Frank"

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A comparison of regression models for static and dynamic prediction of a prognostic outcome during admission in electronic health care records

Autor: Gao, Shan, Albu, Elena, Putter, Hein, Stijnen, Pieter, Rademakers, Frank, Cossey, Veerle, Debaveye, Yves, Janssens, Christel, Van Calster, Ben, Wynants, Laure

Objective Hospitals register information in the electronic health records (EHR) continuously until discharge or death. As such, there is no censoring for in-hospital outcomes. We aimed to compare different dynamic regression modeling approaches to pr

Externí odkaz: http://arxiv.org/abs/2405.01986

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Comparison of static and dynamic random forests models for EHR data in the presence of competing risks: predicting central line-associated bloodstream infection

Autor: Albu, Elena, Gao, Shan, Stijnen, Pieter, Rademakers, Frank, Janssens, Christel, Cossey, Veerle, Debaveye, Yves, Wynants, Laure, Van Calster, Ben

Prognostic outcomes related to hospital admissions typically do not suffer from censoring, and can be modeled either categorically or as time-to-event. Competing events are common but often ignored. We compared the performance of random forest (RF) m

Externí odkaz: http://arxiv.org/abs/2404.16127

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Length of Stay prediction for Hospital Management using Domain Adaptation

Autor: Momo, Lyse Naomi Wamba, Moorosi, Nyalleng, Nsoesie, Elaine O., Rademakers, Frank, De Moor, Bart

Inpatient length of stay (LoS) is an important managerial metric which if known in advance can be used to efficiently plan admissions, allocate resources and improve care. Using historical patient data and machine learning techniques, LoS prediction

Externí odkaz: http://arxiv.org/abs/2306.16823

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Akademický článek

Length of stay prediction for hospital management using domain adaptation

Autor: Momo, Lyse Naomi Wamba, Moorosi, Nyalleng, Nsoesie, Elaine O., Rademakers, Frank, De Moor, Bart

Publikováno v: In Engineering Applications of Artificial Intelligence July 2024 133 Part A

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Akademický článek

A new electric method for non-invasive continuous monitoring of stroke volume and ventricular volume-time curves

Autor: Konings Maurits K, Goovaerts Henk G, Roosendaal Maarten R, Rienks Rienk, Koevoets Ferry M, Bleys Ronald L, Buhre Wolfgang F, Dorresteijn Paul M, Hesselink Tim, Officier Arthur E, Hollenkamp Charles L, Rademakers Frank E

Publikováno v: BioMedical Engineering OnLine, Vol 11, Iss 1, p 51 (2012)

Abstract Background In this paper a new non-invasive, operator-free, continuous ventricular stroke volume monitoring device (Hemodynamic Cardiac Profiler, HCP) is presented, that measures the average stroke volume (SV) for each period of 20 seconds,

Externí odkaz: https://doaj.org/article/296df7d8a9ba4926aa7f22c5de7e98d3

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