I. Bermejo

发表

Systematic review of radiomic biomarkers for predicting immune checkpoint inhibitor treatment outcomes.

A. Dekker, Zhenwei Shi, L. Wee, 2020, Methods.

Digital Health Solutions to Reduce the Burden of Atherosclerotic Cardiovascular Disease Proposed by the CARRIER Consortium

L. Ippel, J. Maessen, M. Spreeuwenberg, 2022, JMIR cardio.

VertiBayes: Learning Bayesian network parameters from vertically partitioned data with missing values

Florian Van Daalen, L. Ippel, I. Bermejo, 2022, ArXiv.

Prediction of Radiotherapy Compliance in Elderly Cancer Patients Using an Internally Validated Decision Tree

J. van Soest, K. Lee, I. Bermejo, 2022, Cancers.

Using clinical prediction models to personalise lifestyle interventions for cardiovascular disease prevention: A systematic literature review

J. Maessen, B. Kietselaer, A. Dekker, 2021, Preventive medicine reports.

Improving reproducibility and performance of radiomics in low‐dose CT using cycle GANs

A. Dekker, L. Wee, I. Bermejo, 2021, Journal of applied clinical medical physics.

Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study pdf

Andre Dekker, Leonard Wee, Inigo Bermejo, 2021, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

How Natural Language Processing Can Aid With Pulmonary Oncology Tumor Node Metastasis Staging From Free-Text Radiology Reports: Algorithm Development and Validation

C. Zegers, I. Bermejo, A. Dekker, 2023, JMIR formative research.

Bayesian network structure for predicting local tumor recurrence in rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery

J. van Soest, A. Dekker, J. Folkesson, 2022, Physics and imaging in radiation oncology.

A comparison of machine learning models for predicting urinary incontinence in men with localized prostate cancer

K. Aben, J. V. van Roermund, R. Verwey, 2023, Frontiers in Oncology.

External Validation of a Bayesian Network for Error Detection in Radiotherapy Plans

Andre Dekker, Wouter van Elmpt, Inigo Bermejo, 2021, IEEE Transactions on Radiation and Plasma Medical Sciences.

Clinical Concept-Based Radiology Reports Classification Pipeline for Lung Carcinoma

L. Wee, C. Zegers, I. Bermejo, 2023, Journal of Digital Imaging.

Using 3D deep features from CT scans for cancer prognosis based on a video classification model: A multi-dataset feasibility study.

L. Wee, I. Bermejo, A. Dekker, 2023, Medical physics.

Lung cancer diagnosis using deep attention‐based multiple instance learning and radiomics

A. Dekker, Zhenwei Shi, L. Wee, 2021, Medical physics.

Artificial intelligence‐based clinical decision support in modern medical physics: Selection, acceptance, commissioning, and quality assurance

Leonard Wee, Andre Dekker, Prasad Rv, 2020, Medical physics.

Identifying Confounders Using Bayesian Networks and Estimating Treatment Effect in Prostate Cancer With Observational Data.

K. Aben, G. Geleijnse, I. Bermejo, 2023, JCO clinical cancer informatics.

Development and validation of deep learning and BERT models for classification of lung cancer radiology reports

I. Bermejo, N. Purandare, S. Mithun, 2023, Informatics in Medicine Unlocked.

Automatic quality assurance of radiotherapy treatment plans using Bayesian networks: A multi-institutional study

W. V. Elmpt, A. Kalet, P. Kalendralis, 2023, Frontiers in Oncology.

Generative models improve radiomics reproducibility in low dose CTs: a simulation study

Andre Dekker, Leonard Wee, Alberto Traverso, 2021, Physics in medicine and biology.

Deep learning based unpaired image-to-image translation applications for medical physics: a systematic review

L. Wee, I. Bermejo, A. Dekker, 2023, Physics in Medicine and Biology.

Are all shortcuts in encoder–decoder networks beneficial for CT denoising?

A. Dekker, L. Wee, Chong Zhang, 2022, Comput. methods Biomech. Biomed. Eng. Imaging Vis..