5th European Congress of Medical Physics

Uncertainty quantification of machine learning models for patient-specific quality assurance prediction

Artificial intelligence

Artificial intelligence (self-study)

Eposter self-study

Clinical radiotherapy

Machine learning model for patient-specific QA prediction in stereotactic radiosurgery

Venus II

Clinical radiotherapy V

Eposter presentation

Fine tuning of deep learning-based optimization of field geometry for total marrow irradiation delivered with volumetric modulated arc therapy

Orion I

Artificial intelligence II

Targeted patient-specific quality assurance supported by machine learning and lean six sigma for volumetric modulated arc therapy plans

Keynote: Implementing AI solutions in daily healthcare by Dr. Kicky van Leeuwen

Artificial intelligence in medical physics: Implementing AI solutions in daily healthcare


Abstract talk

Impact of non-linear resampling to 8-bit CT for total marrow lymph-node irradiation plans

Orion II

Clinical radiotherapy I

Innovative radiotherapy and medical imaging

Machine learning-aided automatable replanning tool to improve the patient-specific quality assurance of modulated radiotherapy plans

Clinical radiotherapy VII

Knowledge-based planning of total marrow lymph-node irradiation delivered with volumetric modulated arc therapy

Keynote: Automated treatment planning – Where will/should it go? by Professor Ben Heijmen

Clinical radiotherapy: Dose calculations

Multicentric evaluation of a machine learning model to streamline the radiotherapy patient specific quality assurance process

more information:<br><br><a href="https://t3-2.conventus-homepages.de/fileadmin/media/ecmp/2024/18th_Enen_PhD_Event_Prize_Students_schedule_v1.pdf" class="extern" target="_blank">ENEN PhD event (pdf)</a>

Nicola Lambri

Speaker

Further involvements