All Meetups
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Towards clinically acceptable deep learning-based auto-contouring for brachytherapy of cervical cancer
by Vangelis Kostoulas from Radiotherapy Department, Leiden University Medical Center
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Deep learning-based automated radiotherapy planning validation for oropharyngeal cancer patients
by Frank Dankers from Radiotherapy Department, Leiden University Medical Center
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Language models in a medical setting
by Liza King from Autoscriber
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Training large language models
by Renzo Scholman from Research Institute for Mathematics & Computer Science (CWI)
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AI and medical liability
by Jan van Staalduinen from Leiden University
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Validation of Transpara, AI for breast cancer detection in mammography and tomosynthesis
by Jaap Kroes & Natasja Janssen from Screenpoint
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Towards a mature AI infrastructure.
by Alexander van Someren from IT&DI department of Leiden University Medical Center
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Contrastive learning for echocardiographic view integration
by Li-Hsin Cheng from Division of Image Processing (LKEB)
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I built an AI model, what's next?
by Floortje Jolink & Bob Vonk from Aidence
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Investigation of the effect of motion on MRI reconstruction, and demostration that finetuning by training with synthetic motion corrupted data can enhance the motion robustness of existing deep learning based reconstruction approaches.
by Laurens Beljaards from Division of Image Processing (LKEB)
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Out-Of-Distribution detection on tabular medical data.
by Giovanni Cinà
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Let have some drinks together!
by LUMC AI Research Meeting Team
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Transformers for Image Segmentations
by Vangelis Kostoulas from Radiotherapy department of Leiden University Medical Center
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Evolutionary Intelligent Bi-objective Treatment Planning for Prostate HDR Brachytherapy
by Anton Bouter
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Evolutionary Intelligence for Image Registration
by Georgios Andreadis & Cedric Rodriguez
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Development and validation of a machine learning model to predict contact moments in post-myocardial infarction home measurements.
by Anne de Hond
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Comparing several types of machine learning models on predictive performance and explainability for the prediction of ICU readmission.
by Siri van der Meijden from Healthplus.ai
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