Intelligent Medical Systems
The NCT Data Science Seminar is a campus-wide effort bringing together thought-leading speakers and researchers in the field of data science to discuss both methodological advances as well as medical applications.
From frustration to improving student education | Katharina Breininger
Beyond Supervised Learning | Bernhard Kainz
All models are wrong and yours are useless | Florian Markowetz
Interactive Segmentation and Annotation of Medical Images| Zdravko Marinov
Reliable and Sustainable AI in Medical Imaging: Successes, Challenges, Limitations | Gitta Kutyniok
Metrics Reloaded Toolkit- A framework for trustworthy image analysis validation
Rankings Reloaded - An open-source toolkit for visualizing benchmarking results
Artificial intelligence-based biomarkers in precision oncology | Jakob Nikolas Kather
Reality-Centric AI & Academia's role in AI in the era of LLMs | Mihaela van der Schaar
Neural and spectral operator surrogates | Jakob Zech
Data replication in medical synthetic image generation using diffusion models | Vishal Patel
Multiscale exploration of single cell data with geometric harmonic analysis | Guy Wolf
Image Denoising and the Generative Accumulation of Photons | Alexander Krull
Image-based Robotic Surgery Intelligence
MICCAI2023 | Self-distillation for surgical action recognition - Yamlahi
MICCAI2023 | Semantic segmentation of surgical hyperspectral images under geometric domain shifts
MICCAI2023 | Unsupervised Domain Transfer with Conditional Invertible Neural Networks - Dreher
MICCAI2023 | Deployment of Image Analysis Algorithms under Prevalence Shifts - Godau & Kalinowski
The role of multiscale modeling in molecular discovery | Tristan Bereau
Medical AI: addressing the validation gap | Gael Varoquaux
Why is the winner the best? - CVPR 2023 | Matthias Eisenmann
Unleashing the Genetic Architecture of Heritable Traits | Christoph Lippert
Advancing deep medical image segmentation with adversarial data augmentation | Chen Chen
Interpretable Representations and Neuro-symbolic Methods in Deep Learning | Jan Stühmer
Neural Causal Models | Stefan Bauer
Best practices for parallelizing data pipelines | Uwe Korn
MDM & OpenEDC: Next-generation study databases in medicine | Martin Dugas
Reverse Engineering the Doctor’s Mind | Anirban Mukhopadhyay
Probabilistic modelling of transcription dynamics in whole embryos and singel cells | Magnus Rattray
(Bench)mark: Pitfalls in AI Validation | Annika Reinke