02:54

Metrics Reloaded Toolkit- A framework for trustworthy image analysis validation

01:44

Rankings Reloaded - An open-source toolkit for visualizing benchmarking results

58:19

Artificial intelligence-based biomarkers in precision oncology | Jakob Nikolas Kather

01:13:02

Reality-Centric AI & Academia's role in AI in the era of LLMs | Mihaela van der Schaar

52:11

Neural and spectral operator surrogates | Jakob Zech

01:02:31

Data replication in medical synthetic image generation using diffusion models | Vishal Patel

01:02:15

Multiscale exploration of single cell data with geometric harmonic analysis | Guy Wolf

57:14

Image Denoising and the Generative Accumulation of Photons | Alexander Krull

54:40

Image-based Robotic Surgery Intelligence

04:51

MICCAI2023 | Self-distillation for surgical action recognition - Yamlahi

04:59

MICCAI2023 | Semantic segmentation of surgical hyperspectral images under geometric domain shifts

05:39

MICCAI2023 | Unsupervised Domain Transfer with Conditional Invertible Neural Networks - Dreher

05:08

MICCAI2023 | Deployment of Image Analysis Algorithms under Prevalence Shifts - Godau & Kalinowski

40:42

The role of multiscale modeling in molecular discovery | Tristan Bereau

56:14

Medical AI: addressing the validation gap | Gael Varoquaux

07:52

Why is the winner the best? - CVPR 2023 | Matthias Eisenmann

51:40

Unleashing the Genetic Architecture of Heritable Traits | Christoph Lippert

55:47

Advancing deep medical image segmentation with adversarial data augmentation | Chen Chen

35:13

Interpretable Representations and Neuro-symbolic Methods in Deep Learning | Jan Stühmer

48:23

Neural Causal Models | Stefan Bauer

40:49

Best practices for parallelizing data pipelines | Uwe Korn

51:04

MDM & OpenEDC: Next-generation study databases in medicine | Martin Dugas

58:16

Reverse Engineering the Doctor’s Mind | Anirban Mukhopadhyay

59:13

Probabilistic modelling of transcription dynamics in whole embryos and singel cells | Magnus Rattray

52:59

(Bench)mark: Pitfalls in AI Validation | Annika Reinke

59:10

Quantum technologies: the second quantum revolution | Tommaso Calarco

50:04

Advances in Scene Reconstruction and Tracking for Endoscopic Surgery | Mathias Unberath

52:34

Highly accurate protein structure prediction with AlphaFold | Simon Kohl

58:41

How can we narrow the gap between human and machine vision | Robert Geirhos

01:01:32

The building blocks of a Big AI in healthcare | Sotirios A. Tsaftaris

57:31

AI-enabled imaging | Julia Schnabel

01:04:01

Data Science for Supporting Molecular Tumor Boards | Ulf Leser

57:40

Trustworthy machine learning in oncology | Florian Büttner

01:08:16

Machine Learning for Single Cell Omics | Jean-Philippe Vert

58:35

Statistical recovery of compositional discrete structures | Merle Behr

21:19

Challenges @ MICCAI 2021 | Lena Maier-Hein & Annika Reinke

57:02

Geometric and Topological Approaches to Representation Learning in Biomed Data | Smita Krishnaswamy

01:03:59

Discovering actionable interpretations from raw visual data: 2D to 3D | Andrea Vedaldi

54:13

Quantifying surgical expertise | Stefanie Speidel

01:00:01

Neighbour embeddings for scientific visualization | Dmitry Kobak

01:02:13

Machine learning at the speed of light | Piotr Antonik

59:22

Improving Transfer Learning via Large-Scale Model Pre-Training | Jenia Jitsev

01:03:42

Natural Language Processing in the Clinical Domain | Phillip Richter-Pechanski

01:02:17

Signed graph partitioning: an important primitive in computer vision | Fred Hamprecht

01:06:21

Federated Learning for Healthcare – Collaborative AI without Sharing Patient Data | Nicola Rieke

01:03:35

What to learn in instrument pose estimation | David Kuegler

59:00

Machine Learning in Medicine: Early Recognition of Sepsis | Karsten Borgwardt

48:52

nnU-Net: Automated Design of Deep Learning Methods for Biomedical Image Segmentation | Paul Jäger

46:38

From development to certified medical product: Bringing ai-solutions to the patient | Phillipp Mann

01:24:00

Deep learning on graphs: successes, challenges, and next steps | Michael Bronstein

01:00:46

Training artificial neural networks with cognitive neuroscience inspired methods | Andreas Krug

01:07:27

Uncertainty, causality and generalization: Improve image-based predictive modelling | Ben Glocker

59:26

Active Invariant Causal Prediction: Experiment Selection through Stability | Christina Heinze-Deml

01:00:03

Deep Learning-based Magnetic Resonance Fingerprinting | Elisabeth Hoppe

01:12:46

Learning Equivariant and Hybrid Message Passing on Graphs | Max Welling