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Frederik A. van Delft

Observed names: F van Delft, F. van Delft, F.A. van Delft, Frederik Van Delft, Frederik van Delft, Freek A. van Delft, Freek van Delft
Observed institutions: Institute of Cancer Research, Queen Mary University of London, University of Cambridge, Leiden University Medical Center, The Netherlands Cancer Institute, University of Twente, Delft University of Technology
ORCID: 0000-0003-3428-6468
Observed ORCID: 0000-0003-3428-6468
OpenAlex ID: A5074935698
Learning from visual force feedback in box trainers: tissue manipulation in laparoscopic surgery
2014 · Tim Horeman, Freek van Delft, et al. · Surgical Endoscopy · 32
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Modeling strategies to analyse longitudinal biomarker data: An illustration on predicting immunotherapy non-response in non-small cell lung cancer
2022 · Frederik A. van Delft, Milou Schuurbiers, et al. · Heliyon · 22
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The Validity and Predictive Value of Blood-Based Biomarkers in Prediction of Response in the Treatment of Metastatic Non-Small Cell Lung Cancer: A Systematic Review
2020 · Frederik van Delft, Hendrik Koffijberg, et al. · Cancers · 10
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Comparing modeling strategies combining changes in multiple serum tumor biomarkers for early prediction of immunotherapy non-response in non-small cell lung cancer
2023 · Frederik A. van Delft, Milou M.F. Schuurbiers, et al. · Tumor Biology · 8
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External validation of a serum tumor marker algorithm for early prediction of no durable benefit to immunotherapy in metastastic non-small cell lung carcinoma
2025 · Milou M. F. Schuurbiers, Freek A. van Delft, et al. · Tumor Biology · 4
Modeling Diagnostic Strategies to Manage Toxic Adverse Events following Cancer Immunotherapy
2021 · Frederik van Delft, Mirte Muller, et al. · Medical Decision Making · 3
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Scenario-based multi-parametric QC for quality control of complex algorithms used in clinical care
2026 · Huub H. van Rossum, Frederik A. van Delft · Clinical Chemistry and Laboratory Medicine (CCLM) · 1
Clinical validation and implementation of mSTOP, a machine learning-based, longitudinal prediction model for the early identification of non-small cell lung cancer patients who not benefit from immune checkpoint inhibitor treatment
2026 · Huub H. van Rossum, Marije van der Schaar, et al. · Clinical Chemistry and Laboratory Medicine (CCLM) · 1
Serological Response Patterns to Assess Treatment Outcomes in Advanced Non-Small Cell Lung Cancer: A Real-World Exploratory Multi-Center Observational Cohort Study
2025 · Alessandra I. G. Buma, Femke Laarakker, et al. · Cancers
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Cost-effectiveness of [18F]FDG PET/CT in follow-up after thermal ablation in patients with colorectal liver metastases in the Dutch healthcare setting
2025 · S. van Mossel, O.D. Bijlstra, et al. · European Journal of Radiology
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Optimizing the use of blood based biomarkers to improve the clinical management of advanced NSCLC
2023 · Frederik van Delft
HTA142 Potential Impact of Biomarker Guided-Decisions on Overtreatment in Immunotherapy for Non-Small Cell Lung Cancer Patients
2022 · F van Delft, H Koffijberg, et al. · Value in Health
194P Modelling strategies to combine multiple serum tumor biomarkers for early prediction of immunotherapy non-response in non-small cell lung cancer
2022 · F. van Delft, M. Schuurbiers, et al. · Annals of Oncology
PCN279 Comparing Methods of Longitudinal SERUM Tumor Marker Analisis in Response Monitoring of Immunotherapy Treated NON-SMALL Cell LUNG Cancer Patients
2020 · F. van Delft, E. Koffijberg, et al. · Value in Health
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Pcn324 Preliminary Evidence Suggests That We Move Towards the Use of Liquid Biopsies to Predict Response to Tki Inhibitors: a Systematic Review
2019 · F. van Delft, E. Koffijberg, et al. · Value in Health
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Op14genetic and Functional Diversity of Propagating Cells in Glioblastoma
2015 · S.G.M. Piccirillo, S. Colman, et al. · Neuro-Oncology
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Atps-93chemo-naïve Glioblastoma Patients Contain Genetically Heterogeneous Sub-clones Capable of Tumour Propagation and Spatially Heterogeneous Drug-resistant Cell Populations
2015 · Colin Watts, Sara Piccirillo, et al. · Neuro-Oncology
Cb-18 * Interrogation of Sub-clonal Genetic Diversity of Human Gbm Reveals Genetic Heterogeneity in Tumour-propagating Cells, Which Display Variable Competitive Capacity for Tumour Propagation in Vivo
2014 · C. Watts, S. Piccirillo, et al. · Neuro-Oncology
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B Precursor ALL Subset with Aberrant CD2 Expression and a Specific Predisposition to Early Monocytic Transdifferentiation
2010 · Ester Mejstrikova, Lucie Slamova, et al. · Blood
A Breakage-Fusion-Bridge Cycle Generated by Telomeric Loss May Underlie the dup(21q) of Acute Lymphoblastic Leukemia.
2005 · Hazel M. Robinson, Christine J. Harrison, et al. · Blood
Works count: 20
Citation count: 81
H-index: 4
I10-index: 3
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