My PhD focuses on the risk and outcome prediction of breast cancer featuring Ductal Carcinoma in Situ (DCIS) in two different modalities, namely histopathology and mammography.
Since starting my PhD in late March 2021, I have worked on the problem of predicting ipsilateral DCIS recurrence in histopathology whole-slide images. This requires advanced (image processing tools (dlup)) and deep learning methods including object detection, classification and self-supervised methods to process the extremely large inputs and extract relevant small-scale and large-scale features.
In collaboration with the Radboud UMC in Nijmegen, I will develop deep learning methods to identify calcified lesions with a low harm risk during breast cancer screening from mammography data.
About myself:
I have accumulated experience and knowledge in biomedicine, bioinformatics, entrepreneurship, and AI. My aim is to use and combine these skills to make a positive impact for human health.
Since starting my PhD in late March 2021, I have worked on the problem of predicting ipsilateral DCIS recurrence in histopathology whole-slide images. This requires advanced (image processing tools (dlup)) and deep learning methods including object detection, classification and self-supervised methods to process the extremely large inputs and extract relevant small-scale and large-scale features.
In collaboration with the Radboud UMC in Nijmegen, I will develop deep learning methods to identify calcified lesions with a low harm risk during breast cancer screening from mammography data.
About myself:
I have accumulated experience and knowledge in biomedicine, bioinformatics, entrepreneurship, and AI. My aim is to use and combine these skills to make a positive impact for human health.
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