P M A van Ooijen
Overview
Explore the profile of P M A van Ooijen including associated specialties, affiliations and a list of published articles.
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Citations
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Recent Articles
1.
Neh H, de Vette S, Stoffers R, Zhou G, van Ooijen P, Sijtsema N, et al.
Radiother Oncol
. 2025 Jan;
205:110746.
PMID: 39884394
Background/purpose: Taste impairment is a common yet complex toxicity of head and neck cancer (HNC) radiotherapy treatment that may affect quality of life of survivors. This study aimed to predict...
2.
de Groot T, Sommerkamp A, Thio Q, Karhade A, Groot O, Oosterhof J, et al.
Acta Orthop Belg
. 2025 Jan;
90(3):493-501.
PMID: 39851022
Accurate survival prediction of patients with long-bone metastases is challenging, but important for optimizing treatment. The Skeletal Oncology Research Group (SORG) machine learning algorithm (MLA) has been previously developed and...
3.
Darzi E, Shen Y, Ou Y, Sijtsema N, van Ooijen P
Artif Intell Med
. 2024 Jul;
155:102936.
PMID: 39079202
Federated learning enables training models on distributed, privacy-sensitive medical imaging data. However, data heterogeneity across participating institutions leads to reduced model performance and fairness issues, especially for underrepresented datasets. To...
4.
Darzi E, Sijtsema N, van Ooijen P
Sci Rep
. 2024 Feb;
14(1):3944.
PMID: 38365940
Deep learning has proven to be highly effective in diagnosing COVID-19; however, its efficacy is contingent upon the availability of extensive data for model training. The data sharing among hospitals,...
5.
Darzidehkalani E, Ghasemi-Rad M, van Ooijen P
J Am Coll Radiol
. 2022 Apr;
19(8):969-974.
PMID: 35483439
With recent developments in medical imaging facilities, extensive medical imaging data are produced every day. This increasing amount of data provides an opportunity for researchers to develop data-driven methods and...
6.
Darzidehkalani E, Ghasemi-Rad M, van Ooijen P
J Am Coll Radiol
. 2022 Apr;
19(8):975-982.
PMID: 35483437
Federated learning is a machine learning method that allows decentralized training of deep neural networks among multiple clients while preserving the privacy of each client's data. Federated learning is instrumental...
7.
van den Oever L, Spoor D, Crijns A, Vliegenthart R, Oudkerk M, Veldhuis R, et al.
J Med Syst
. 2022 Mar;
46(5):22.
PMID: 35338425
Cardiac structure contouring is a time consuming and tedious manual activity used for radiotherapeutic dose toxicity planning. We developed an automatic cardiac structure segmentation pipeline for use in low-dose non-contrast...
8.
van den Oever L, van Veldhuizen W, Cornelissen L, Spoor D, Willems T, Kramer G, et al.
J Digit Imaging
. 2022 Jan;
35(2):240-247.
PMID: 35083620
Organs-at-risk contouring is time consuming and labour intensive. Automation by deep learning algorithms would decrease the workload of radiotherapists and technicians considerably. However, the variety of metrics used for the...
9.
Olthof A, van Ooijen P, Cornelissen L
J Med Syst
. 2021 Sep;
45(10):91.
PMID: 34480231
In radiology, natural language processing (NLP) allows the extraction of valuable information from radiology reports. It can be used for various downstream tasks such as quality improvement, epidemiological research, and...
10.
Olthof A, Shouche P, Fennema E, IJpma F, Koolstra R, Stirler V, et al.
Comput Methods Programs Biomed
. 2021 Aug;
208:106304.
PMID: 34333208
Objectives: To compare different Machine Learning (ML) Natural Language Processing (NLP) methods to classify radiology reports in orthopaedic trauma for the presence of injuries. Assessing NLP performance is a prerequisite...