PHOTOGRAPHY KEE AND KEE // MODEL LISANNE VAN DIJK IBTM MODELS EDITORIAL in 2019 Fur coat
Lisanne V van Dijk 1 , Charlotte L Brouwer 2 , Arjen van der Schaaf 2 , Johannes G M Burgerhof 3 , Roelof J Beukinga 2 , Johannes A Langendijk 2 , Nanna M Sijtsema 2 , Roel J H M Steenbakkers 2 Affiliations 1 Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands. Electronic address: l.v.
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Lisanne van Dijk. 0000-0002-9515-5616. Follow. Publications. Black bone MRI morphometry for mandibular cortical bone measurement in head and neck cancer patients: Prospective method comparison with CT; Precision association of lymphatic disease spread with radiation-associated toxicity in oropharyngeal squamous carcinomas;
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PMCID: PMC8906058 DOI: 10.1016/j.ijrobp.2021.04.042 Abstract Purpose: Osteoradionecrosis (ORN) of the mandible represents a severe, debilitating complication of radiation therapy (RT) for head and neck cancer (HNC). At present, no normal tissue complication probability (NTCP) models for risk of ORN exist.
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Read Lisanne van Dijk's latest research, browse their coauthor's research, and play around with their algorithms
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Lisanne V van Dijk. Assistant Professor at UMCG. Verified email at umcg.nl. Radiomics NTCP TCP modeling Image Biomarkers Proton therapy multi-modality imaging. Articles Cited by Public access.. W Schaake, A van der Schaaf, LV van Dijk, ACM van den Bergh,. PLoS One 13 (7), e0197757, 2018. 33: 2018:
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PMID: 31653573 DOI: 10.1016/j.radonc.2019.09.022 Abstract Introduction: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects.
Lisanne VAN DIJK PostDoc Position Doctor of Medicine University of Texas MD Anderson
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Lisanne van Dijk dr.. https://orcid.org/0000-0002-9515-5616 Overview Network Research output (74) Activities (8) Prizes (4) If you made any changes in Pure these will be visible here soon. Collaborations and top research areas from the last five years Recent external collaboration on country/territory level.
Lisanne van Dijk is 29 jaar, getrouwd en moeder van drie dochters. Sinds vier jaar is ze bewust
UMCG; MDACC - Cited by 3,584 - Radiomics - NTCP TCP modeling - Image Biomarkers - Proton therapy - multi-modality imaging
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Lisanne V van Dijk 1 , Maria Thor 2 , Roel J H M Steenbakkers 3 , Aditya Apte 2 , Tian-Tian Zhai 3 , Ronald Borra 4 , Walter Noordzij 5 , Cherry Estilo 6 , Nancy Lee 7 , Johannes A Langendijk 3 , Joseph O Deasy 2 , Nanna M Sijtsema 3
Lisanne van Dijk De Haagse Hogeschool / The Hague University of Applied Sciences Tilburg
Lisanne van Dijk PhD, University Medical Center Groningen (UMCG) Many head and neck cancer patients suffer from persistent severe toxicities following radiotherapy. As survival rates increase, toxicity reduction has become more pivotal. This project uses Artificial Intelligence techniques to predict toxicity trajectories, which can facilitate.
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Lisanne V. van Dijk. Department of Radiation Oncology, The University of Texas MD Anderson Cancer, 77030, Houston, TX, USA, Clifton D. Fuller. Department of Radiation Oncology, The University of Texas MD Anderson Cancer, 77030, Houston, TX, USA
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In short, Lisanne van Dijk's research entails the following: Deep learning to Enhance Therapeutic Outcomes and toXicity for LUNG cancer patients (DETOX-LUNG) Radiotherapy is an important treatment for lung cancer patients, yet they are often faced with severe toxicities due to radiation damage. These toxicities do not only have a big impact on.
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Lisanne V. van Dijk is an academic researcher from University of Texas MD Anderson Cancer Center. The author has contributed to research in topics: Medicine & Head and neck cancer. The author has an hindex of 14, co-authored 45 publications receiving 1365 citations.
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Dr. van Dijk's formal education as a Technical Physician gives uniquely positions her to translate technical innovations to clinic-usable applications. Her PhD is in radiomics and machine learning approaches to predict of radiation-induced toxicities and tumor outcome with multi-modality imaging in head and neck cancer patient.
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dr. L.V. (Lisanne) van Dijk Assistant Professor Faculty of Medical Sciences Telephone: E-mail: [email protected] Publications Publications Comparison of computed tomography image features extracted by radiomics, self-supervised learning and end-to-end deep learning for outcome prediction of oropharyngeal cancer