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, a novel spatial discovery proteomics concept that integrates microscopic cell phenotyping with deep-learning based image analysis and global MS-based proteomics. This unique method was recently
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of methods for anomaly detection and disease recognition based on learned normative representations • Development of vision-language models for clinical reasoning and interpretable reporting of medical imaging
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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to streamflow as a function of climate and landscape controls, using deep learning and explainable AI Communicate and discuss results with stakeholders to integrate the findings into water management