🎉 Update: This work got accepted to #icml2025!!
Huge thanks to my amazing co-authors @LorenzLinhardt, Marco Morik, @jdppel, @skornblith, and @lukas_mut for their great work and to all collaborators! 🙏
📄 Paper: https://t.co/XqRNulzfK9
💻 Code: https://t.co/cLlxnYUojs
🧵1/3
Mayo Clinic announced the formation of Mayo Clinic Digital Pathology, designed on a platform architecture to boldly unlock the power of its extensive archive of digital slides to revolutionize pathology and accelerate medical breakthroughs.
Learn more: https://t.co/LFPEOAtIiE
Original Article by @jdppel et al.: AI-Based Anomaly Detection for Clinical-Grade Histopathological Diagnostics https://t.co/u1NxNPIuZu
#ArtificialIntelligence
A deep anomaly detection approach for histopathology shows high detection performance for a broad range of diseases (including all cancers) within the long diagnostic tail in gastrointestinal biopsies. Read the full article by @jdppel et al.: https://t.co/u1NxNPIuZu
If two models are more similar to each other than a third on ImageNet, will this hold for medical/ satellite images? Our preprint analyzes how vision model similarities generalize across datasets, the factors that influence them, and their link to downstream task behavior. 🧵1/7
Our work on historical insights at scale using machine learning is now out in @ScienceAdvances! Very proud of this team effort, bridging disciplines and institutions—@MPIWG @TUBerlin@bifoldberlin@ml_tuberlin
📜https://t.co/pLWBmCa2W5
🧵I am excited to share that our paper: AI-Based Anomaly Detection for Clinical-Grade Histopathological Diagnostics has now been published in @NEJM_AI .
https://t.co/GsQLrfTb0x
🙏 Thanks to my co-first author @n_prenissl , stellar supervision by @lukasruff , Klaus-Robert Müller, @FKlauschen and amazing contributions by @hense96, Philipp Liznerski, Tobias Winterhoff, Simon Schallenberg, Marius Kloft, Oliver Buchstab, David Horst, and Maximilian Alber.
Why do some memories fade in seconds, while others stay with us for life? Working Memory (WM) holds info for just moments, but certain bits manage to stick around and make it into Long-Term Memory (LTM). In our new ⚡️preprint⚡️, we examined what helps these memories stick. 1/
The #aignostics team is heading to #ASCO2024!
Interested in hearing about how we’re transforming precision medicine with our industry-leading foundation model and advanced machine learning algorithms? Let’s connect on June 2-3: https://t.co/ObHQGsTrbl
#ASCO24#PrecisionMedicine
The camera-ready version is now available on arXiv! 🔥 We've updated our manuscript with results for a few interesting experiments that were suggested by the reviewers during the rebuttal period. See the thread below👇
🎇 We have another opening for a PhD student position in the @bifoldberlin agility project 'LungCAIRE' with Charité on multimodal data representations for lung cancer relapse prediction and related use cases:
https://t.co/aGlgLyNRtv
(application deadline: Sep 08, 2023)
We have a new website 🎉
Thanks to all the people who put countless hours into making it look as amazing as it does!
Want to learn more about our team, #research, open positions and offered courses?
Check it out 👉 https://t.co/zQJozOBcIJ
#MachineLearning#Berlin