جست‌وجوی استاد و پژوهشگر

• Radiation Oncology
• Head and Neck Oncology
• Proton Therapy
• +۳ مورد دیگر

Prof. dr. Hans Langendijk is a Professor and Chair of the Department of Radiation Oncology at the University of Groningen's Faculty of Medical Sciences. He holds additional roles including Chair of the Oncology Division at UMCG and membership in international advisory boards such as the Danish Center for Particle Therapy and the EU HARMONIC project. His research focuses on Radiation Oncology, particularly in Head and Neck Oncology and Proton Therapy applications. He has contributed to advancements in normal tissue complication probability (NTCP) modeling and radiation-induced toxicity studies. Notable awards include the Jens Overgaard Legacy Award and the Carl Krebs Award. His research spans topics like subclinical cardiac dysfunction post-irradiation, proton therapy dosimetry, and predictive modeling for treatment outcomes. Langendijk has been actively involved in international collaborations, including studies on proton therapy efficacy and radiation-induced complications. He has supervised 40+ academic works and contributed to numerous peer-reviewed publications in journals like Radiology: Cardiothoracic Imaging and Radiotherapy and Oncology . Awards include recognition for his contributions to radiation oncology and clinical research. His work aligns with UN Sustainable Development Goals related to health and well-being, emphasizing evidence-based practices in oncology treatment and patient outcomes.

• Radiation Oncology
• Stereotactic Body Radiation Therapy
• Lung Cancer
• +۷ مورد دیگر

Marloes Duijm is a researcher at Erasmus MC in the Department of Radiotherapy, affiliated with Erasmus Universiteit Rotterdam. Her work is centered on advancing radiation therapy techniques for lung cancer, particularly through stereotactic body radiotherapy (SBRT). Her research interests focus on improving clinical outcomes for patients with early-stage and centrally located lung tumors. She specializes in developing and validating prognostic models and nomograms to predict overall survival and treatment-related toxicities. Her work integrates clinical data with statistical modeling to personalize radiotherapy planning and improve patient stratification. The recent publications of Marloes Duijm demonstrate a strong trend in radiation oncology, particularly in the application of SBRT for non-small cell lung cancer and ultra-central tumors. Her research emphasizes predictive modeling for survival and toxicity, leveraging large clinical datasets for external validation. These studies contribute significantly to evidence-based radiotherapy protocols. Marloes Duijm has not been publicly recognized with any scientific awards based on the available information. She completed her doctoral thesis in 2021 at Erasmus Universiteit Rotterdam, titled "Outcome and Toxicity Modelling after Stereotactic Radiotherapy of Central Lung Tumors." There is no mention of her advising students or receiving research grants in the provided texts. While her research is closely tied to the Radiotherapy department at Erasmus MC, there is no explicit mention of her leading a lab or a dedicated research team. Her collaborative publications suggest active participation in a broader research network within the institution.

Kylie Keijzerمشاهده پروفایل

پژوهشگر

• Immunology
• Oncology
• Hematology
• +۳ مورد دیگر

Kylie Keijzer is a researcher actively contributing to oncology, hematology, and immunotherapy. Her work focuses on improving clinical outcomes through studies on CAR T-cell therapy for large B-cell lymphoma, tumor volume analysis, and toxicity risk profiling in head and neck cancer patients. She has also investigated metabolic complications like severe hyperglycemia during hematological care. Research areas include: Development of Normal Tissue Complication Probability (NTCP) models for head and neck cancer Role of serum TARC as a biomarker in Hodgkin lymphoma relapse detection Metabolic active tumor volume control to enhance CAR T-cell therapy survival outcomes Prospective glucose monitoring studies in hematological patients Her collaborations span international institutions, aligning with UN Sustainable Development Goals related to health and well-being (SDG 3) and global partnerships (SDG 17).

• Radiation Oncology
• Machine Learning in Healthcare
• Medical Imaging
• +۴ مورد دیگر

Hung Chu is an active researcher contributing to interdisciplinary fields at the intersection of medical imaging, radiation oncology, and machine learning. His work focuses on developing predictive models for radiation therapy complications in head and neck cancer patients, while also exploring machine learning applications in pediatric pulmonary hypertension and multimorbidity healthcare utilization. Developed deep learning NTCP models for dysphagia and xerostomia prediction in radiotherapy patients Validated international cohorts for radiation toxicity modeling Applied machine learning to cardiac MRI analysis for pulmonary hemodynamics Created predictive models for healthcare utilization in multimorbidity patients His research spans multiple disciplines including medical imaging analysis, clinical decision support systems, and healthcare informatics. Recent publications demonstrate expertise in 3D dose modeling, radiomics, and transfer learning applications in medicine. Collaborations include international institutions and multidisciplinary teams across radiation oncology, cardiology, and healthcare management. While no specific awards are mentioned, the open-access nature of publications indicates strong academic engagement.

• Head and Neck Cancer
• Radiation Therapy
• Dysphagia
• +۷ مورد دیگر

Roel Steenbakkers is a researcher at the Faculty of Medical Sciences , University of Groningen , affiliated with the Personalized Cancer Treatment group. His work focuses on Head and Neck Cancer , Radiation Therapy , and Dysphagia management, particularly in developing and refining Normal Tissue Complication Probability (NTCP) models to predict treatment side effects. His research contributes to UN Sustainable Development Goals (SDGs), particularly those related to health and well-being. Key areas of expertise include Chemoradiotherapy , Xerostomia mitigation, and Proton Therapy optimization. Recent publications highlight advancements in deep learning-based NTCP models , frailty assessment in cancer patients, and aspiration risk prediction through dose-volume analysis. He actively collaborates on international cohorts and clinical trials, including studies on Ledderhose disease and radiation-induced toxicity .

Gert Sikkemaمشاهده پروفایل

پژوهشگر

• Astronomy
• Astrophysics
• Galaxy Evolution
• +۵ مورد دیگر

Dr. Gert Sikkema is a researcher at the Faculty of Medical Sciences, University of Groningen, with a unique interdisciplinary profile spanning astronomy, medical physics, and ancient history. His work demonstrates significant contributions to both astronomical surveys and medical radiotherapy research. His research interests include galaxy evolution, astronomical data processing, medical visualization, DICOM applications, anonymization of patient data, and DVH calculations for radiotherapy. Sikkema has made substantial contributions to major astronomical projects including the Kilo-Degree Survey (KiDS), the SAMI Galaxy Survey, and the Euclid mission. In medical physics, he focuses on radiation therapy effects, particularly studying how irradiation of organs at risk affects survival in breast cancer patients and developing NTCP models for coronary events. His recent publications show a clear trend toward interdisciplinary work that bridges astronomy data processing techniques with medical physics applications. The 2024 Euclid mission overview paper represents cutting-edge space telescope research, while his concurrent medical physics publications demonstrate practical applications in cancer treatment. Selected to be designated as a 2020 Best of ASTRO abstract Sikkema's work spans multiple research domains, with significant contributions to astronomical survey methodology and medical physics applications. His research demonstrates how data processing techniques developed for astronomy can be applied to medical imaging and treatment planning problems.

• Radiation Oncology
• Head and Neck Cancer
• Normal Tissue Complication Probability (NTCP) Modeling
• +۳ مورد دیگر

Suzanne Rozema-de Vette is a Lecturer at the University of Twente (UTwente) and a researcher affiliated with the Division of Radiation Oncology at The University of Texas MD Anderson Cancer Center. Her work focuses on developing and validating Normal Tissue Complication Probability (NTCP) models using deep learning and medical imaging to predict radiation therapy toxicities in head and neck cancer patients. Key research areas: Head and Neck Cancer, Radiation Therapy, Deep Learning Applications Primary affiliations: MD Anderson Cancer Center, UTwente Her research addresses SDGs related to good health and well-being through precision oncology advancements. She has presented her work internationally, including at MD Anderson Cancer Center, and contributes to multi-institutional studies like PREDMORN. Recent publications demonstrate expertise in predicting late dysphagia, xerostomia, and osteoradionecrosis using 3D dose distributions and CT imaging. Collaborations span institutions in Europe and the U.S., emphasizing global integration of radiation therapy models.

• Head and Neck Cancer
• Radiation Therapy
• Proton Therapy
• +۳ مورد دیگر

Hans Paul van der Laan is a researcher at the University of Groningen's Faculty of Medical Sciences, specializing in the Personalized Cancer Treatment department. His work focuses on optimizing radiation therapy protocols for head and neck cancer patients through advanced modeling techniques. His research interests center on precision oncology, particularly: Head and neck cancer treatment optimization Radiation-induced toxicity prediction Frailty assessment in cancer patients Normal tissue complication probability modeling Aspiration risk reduction strategies Proton therapy applications His publications demonstrate consistent focus on improving patient outcomes through quantitative modeling of radiation effects. His recent publications reveal strong emphasis on interdisciplinary approaches combining medical physics, geriatric assessment, and clinical oncology. Key trends include development of NTCP models for dysphagia and aspiration, integration of frailty metrics into treatment planning, and international validation of radiation protocols. Hans Paul van der Laan has supervised at least one research project as indicated by institutional records. His collaborative network spans multiple international institutions focused on head and neck cancer research. He actively contributes to the Personalized Cancer Treatment research group at UMCG, which develops advanced radiation therapy protocols using computational modeling and clinical data analysis to minimize treatment complications while maintaining efficacy.

Arjen van der Schaafمشاهده پروفایل

پژوهشگر

• Radiation Oncology
• Medical Imaging
• Treatment Effects Modeling
• +۳ مورد دیگر

Dr. Arjen van der Schaaf is a medical physicist affiliated with the University of Groningen , working within the Faculty of Medical Sciences through the Personalized Cancer Treatment (PCT) and BRIDGE research groups. His research focuses on optimizing radiation therapy through advanced imaging and modeling of treatment effects, particularly in head and neck cancer and proton therapy applications. His work intersects with critical subfields including NTCP model development , aspiration risk prediction , dysphagia toxicity analysis , and radiation-induced contrast enhancement . Key collaborations span institutions like UMCG, with emphasis on international cohort studies and multi-institutional validation . Notable contributions include: Development of predictive models for radiation-induced complications in brain tumors and mandibular health Improvement of NTCP frameworks for aspiration and swallowing disorders Integration of proton therapy dosimetry with clinical outcomes His research directly supports the UN Sustainable Development Goal 3 (Good Health and Well-being) , focusing on reducing radiation therapy side effects while improving efficacy.

Nanna Maria Sijtsemaمشاهده پروفایل

پژوهشگر

• Radiotherapy
• Adaptive Radiotherapy (ART)
• Image Biomarkers
• +۷ مورد دیگر

Nanna Maria Sijtsema is a researcher specializing in radiotherapy and oncological imaging. Her work focuses on adaptive radiotherapy techniques, image biomarkers, and radiomics applications in cancer treatment. She has contributed to studies on head and neck cancer, proton therapy optimization, and normal tissue complication probability (NTCP) modeling. Sijtsema holds an editorial role at the journal Physica Medica . Her research interests include improving treatment outcomes through precision radiation oncology, integrating AI-driven imaging solutions, and predicting treatment-related side effects. Key collaborations involve international cohorts in head and neck cancer studies and proton therapy validation. Notable contributions include developing MRI-based tumor segmentation algorithms and evaluating PET/CT biomarkers for outcome prediction. She received recognition as a 2020 Best of ASTRO abstract recipient for collaborative work on radiation dose optimization in breast cancer patients.