katherlab @katherlab
Research group "Clinical Artificial Intelligence" @Medizin_TUD @tudresden_de, led by @jnkath kather.ai Dresden Joined July 2023-
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Twitter is really becoming unbearable. I fully support keeping science separate from politics, but this is going too far. Foreign oligarchs should not be influencing European politics. I’ll still be around here, but my main activity is now on 🦋👇
Very happy to share our article about AI agents in cancer research and oncology, with @LeeTaliq @Dykex6 & Aviv Regev, out in @NatureCancer now -> nature.com/articles/s4301… @katherlab @NCT_UCC_DD @NCT_HD
Happy to share a new review article led by Laura @zigutyte from @Katherlab. We surveyed all contributions at Europe’s largest conference on hepatology, @EASLnews 2024. The liver research field is already integrating AI techniques for diagnostics, evaluating treatment effectiveness, assessing risks, and more. buff.ly/40J3DAi
Today, we hosted the first conference on LLMs in medicine at @katherlab / @tudresden_de, chaired by @IsabellaWies 🤩 We are not just riding the hype train🚆 - we are working hard to provide scientific & clinical evidence for benefits and limitations of LLMs in healthcare
We had a fun session on artificial intelligence at the @dgho_eV German/Swiss/Austrian conference of #hematology and #oncology in Basel 🇨🇭Both the main room and the overflow room were overflowing ... thanks to excellent speakers @leukaemielabor @C_V_Schneider & others
New paper from @katherlab led by @ElNahhasOSM et al. 😊👇
#NewNProt moves from whole-slide image to #biomarker prediction: end-to-end weakly-supervised #deeplearning in #computationalpathology bit.ly/3zoUh1w
New research from @katherlab led by @IsabellaWies 🤩
This study developed an open-source tool using a LLM to extract important medical information from clinical text, focusing on decompensated #LiverCirrhosis. The tool identified liver cirrhosis from free text with 100% sensitivity and 96% specificity, and showed strong results
New article from @katherlab in @NatureMedicine: large language models for interoperability in healthcare 👇
In the era of large language models: "The extensive efforts previously required to standardize and make coding systems and ontologies interoperable for traditional computing are no longer necessary." nature.com/articles/s4159… by @jnkath @DanielTruhn @Dykex6 @IsabellaWies
This week was about research. It is inspiring to see how people come together, clinicians with computational scientists, all with a common goal, to help cancer patients on their journey. Together, we are better! Thanks, @jnkath, for organizing a great AI in medicine week.
Exciting new research by @ElNahhasOSM from @katherlab 🤩
Excited to present my latest work accepted in #MICCAI2024 on joint multi-task learning in computational pathology! We reach SOTA performance on predicting MSI and HRD status by learning auxiliary regression tasks related to the tumor microenvironment 🔬 arxiv.org/abs/2403.03891
New research from @katherlab, led by @JClusmann : "Prompt Injection Attacks on Large Language Models in Oncology" arxiv.org/abs/2407.18981 We show that vision-language models in oncology can be attacked easily, creating malicious output which could harm patients. @tudresden_de @NCT_UCC_DD @NCT_HD @EKFZdigital @DKFZ
Just out from @katherlab 👇
This review explores the transition of deep learning in radiology from laborious fully supervised methods to more scalable weakly supervised methods. @laim_uka @ekfzdigital @jnkath @katherlab @danieltruhn @LeoMisera @FranzesGustav bit.ly/4fmDrjR
New research led by @ChiaraMLL 🤩
Happy to share a new computational pathology preprint from @katherlab & many other groups: "HIBRID - Histology and ct-DNA based Risk-stratification with Deep Learning". Deep Learning 💻+ ctDNA 🧬= very powerful prognostic model in colorectal cancer ☑️ medrxiv.org/cgi/content/sh…
New preprint from @katherlab: large language models for end-to-end clincial trial matching. Our system parses study protocols and patient records, and matches them. We evaluate thoroughly against human experts and find >90% correspondence. Led by @Dykex6 🤩 arxiv.org/abs/2407.13463 @NCT_UCC_DD @NCT_HD @DKFZ @DataScienceDKFZ @uniklinik_hd @myESMO CC @tompowles1 @NEJM_AI @Agrawal_Mri @alexia_zz @PepPamies
Weekend read: We are discussing the future of AI in cancer research in @Cancer_Cell sciencedirect.com/science/articl… ... with @MoritzGerstung @james_y_zou @MarzyehGhassemi @diegochowell @jonasteuwen @AI4Pathology 🤩 @NCT_UCC_DD @nct_hd @DKFZ @uniklinik_hd @tudresden_de
New preprint from @katherlab, led by @IsabellaWies - large language models can solve one of the hardest problems in medical informatics - robustly anonymizing unstructured medical documents. This unlocks a large source of clinical data for downstream AI applications. Available open source. @NCT_UCC_DD @DKFZ @NCT_HD @tudresden_de @prof_ebert @NEJM_AI @EricTopol @Medizin_TUD
Allow me to introduce: the #LLM-Anonymizer - our LLM-based solution that enables the #anonymization of medical documents📄! @jnkath @katherlab @Dykex6 medrxiv.org/cgi/content/sh…
So proud of @IsabellaWies from @tudresden_de and @unimedizinma who is presenting about the “skill of prompt engineering” at our AI session at @EASLedu #EASLcongress
Happening now at #EASLcongress 2024: "Research in the Era of AI" in the Gold Room. Discover how artificial intelligence is transforming scientific inquiry with talks on AI's impact, literature reviews, prompt engineering, and scientific integrity. @jnkath @tom_marjot
What a fun session at @EASLedu @EASLnews #EASLcongress 2024 about "Research in the age of AI" in Milan 🇮🇹🇪🇺. Any biomedical researcher should be aware of current AI tools and develop a basic literacy. @tudresden_de @NCT_UCC_DD @NCT_HD @Medizin_TUD @uniklinik_hd
Out today in @Nature - a broad overview of AI in oncology, happy to have contributed to this along with many colleagues and friends @PrelajArsela @anantm & others
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