Uzay Kaymak
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Explore the profile of Uzay Kaymak including associated specialties, affiliations and a list of published articles.
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17
Citations
61
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Recent Articles
1.
Bakkes T, Mestrom E, Ourahou N, Kaymak U, de Andrade Serra P, Mischi M, et al.
Perioper Med (Lond)
. 2024 Jul;
13(1):66.
PMID: 38956723
Objective: This paper presents a comprehensive analysis of perioperative patient deterioration by developing predictive models that evaluate unanticipated ICU admissions and in-hospital mortality both as distinct and combined outcomes. Materials...
2.
Zhang S, Genga L, Dekker L, Nie H, Lu X, Duan H, et al.
J Biomed Inform
. 2023 Dec;
149:104566.
PMID: 38070818
Modern hospitals implement clinical pathways to standardize patients' treatments. Conformance checking techniques provide an automated tool to assess whether the actual executions of clinical processes comply with the corresponding clinical...
3.
F de Carvalho D, Kaymak U, van Gorp P, van Riel N
BMC Med Inform Decis Mak
. 2023 Dec;
23(1):282.
PMID: 38066494
Background: In the Diabetes domain, events such as meals and exercises play an important role in the disease management. For that, many studies focus on automatic meal detection, specially as...
4.
Rijcken E, Kaymak U, Scheepers F, Mosteiro P, Zervanou K, Spruit M
Front Big Data
. 2022 May;
5:846930.
PMID: 35600326
The clinical notes in electronic health records have many possibilities for predictive tasks in text classification. The interpretability of these classification models for the clinical domain is critical for decision...
5.
Fuchs C, Nobile M, Zamora G, Degeneffe A, Kubben P, Kaymak U
BMC Bioinformatics
. 2021 Apr;
22(Suppl 2):57.
PMID: 33902458
Background: Tremor severity assessment is an important step for the diagnosis and treatment decision-making of essential tremor (ET) patients. Traditionally, tremor severity is assessed by using questionnaires (e.g., ETRS and...
6.
Chen P, Dong W, Wang J, Lu X, Kaymak U, Huang Z
BMC Med Inform Decis Mak
. 2020 Jul;
20(Suppl 3):131.
PMID: 32646437
Background: The interpretability of results predicted by the machine learning models is vital, especially in the critical fields like healthcare. With the increasingly adoption of electronic healthcare records (EHR) by...
7.
Nuijten R, Van Gorp P, Kaymak U, Simons M, Kemperman A, van den Berg P
Annu Int Conf IEEE Eng Med Biol Soc
. 2020 Jan;
2019:3600-3604.
PMID: 31946656
Despite the many mHealth solutions available, it remains unclear what their success factors are. Specifically, there has been controversy on the effectiveness of extrinsic rewards. This study evaluates two design...
8.
van Loon S, Deneer R, Nienhuijs S, Wilbik A, Kaymak U, van Riel N, et al.
Obes Surg
. 2019 Nov;
30(2):714-724.
PMID: 31724117
Purpose: The focus of bariatric surgery is reduction of weight, reflected in body mass index (BMI). However, the resolution of comorbidity is a second important outcome indicator. The degree of...
9.
Chen P, Dong W, Lu X, Kaymak U, He K, Huang Z
J Biomed Inform
. 2019 Oct;
100:103303.
PMID: 31610264
Utilizing clinical observational data to estimate individualized treatment effects (ITE) is a challenging task, as confounding inevitably exists in clinical data. Most of the existing models for ITE estimation tackle...
10.
Fuchs C, Celik B, Brouns S, Kaymak U, Haak H
PLoS One
. 2019 Jan;
14(1):e0210743.
PMID: 30699209
Emergency care in elderly patients has gained attention by researchers due to high utilization rate and the importance of emergency services in elderly care. We examine if there is a...