Clinical Artificial Intelligence
We are a young, diverse, and interdisciplinary group of scientists. We use computational methods to extract actionable knowledge from clinical routine data. Our main tools are Artificial Intelligence and Computational Modeling. We combine these tools with a clinical perspective on health and disease. Our main area of expertise is precision oncology of solid tumors, including immunotherapy. We are global thought leaders in the area of predicting clinically actionable properties of tumors directly from routinely available histopathology slides. Our lab’s mission is to build an interdisciplinary space in which young biologists, medical doctors and computer scientists collaborate and co-develop ideas and methods for improved clinical decision making in cancer.
The amount of routinely available data in oncology is massively increasing. Currently, we are not using this data for clinical decision making. At the same time, in data science, we are witnessing an exponential increase of state-of-the-art deep learning (DL), especially self-supervised models, transformers and generative models. In just five years, these algorithms have massively pushed the boundary of what was technically feasible to completely new levels. However, as the fields of medicine and data science evolve faster and faster, they are becoming increasingly disconnected. Without structured efforts, it is hard to keep up to date in both fields.
- Develop new AI-based methods for clinical use, actually integrate AI into clinical practice, and respect patient privacy and needs
- Artificial intelligence and machine learning are helping to identify patterns in medical data and develop personalized therapy recommendations. By using AI in clinical practice, cancer could be detected more quickly in the future, the subtype broken down and the disease treated more effectively.
- Build an interdisciplinary space where young scientists collaborate and co-develop ideas and methods for improved clinical decision making in cancer
Lab members
find overview https://jnkather.github.io/team/
© Anja Stübner
Group leader
NameProf. Dr. med. Jakob Kather
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POSITIONS AND EDUCATION |
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| since 06/2022 | Full Professorship (W3) for “Clinical Artificial Intelligence” at Technical University of Dresden, Germany |
| 2021 - 2022 | Junior (Assistant) Professorship (W1 with tenure track to W2) at the Medical Faculty of RWTH University Aachen, Germany |
| 2021 - present | Visiting Associate Professor in the School of Medicine, Leeds Institute of Medical Research at St James's, University of Leeds, United Kingdom |
| 2019 - 2022 | Research Group Leader “Computational Oncology” at University Hospital RWTH Aachen, Aachen, Germany |
| 2018 - 2022 |
Resident Physician in Gastroenterology, Gastrointestinal Oncology, Medical Intensive Care at University Hospital RWTH Aachen, Aachen, Germany |
| 2016 - 2018 | Resident Physician, Medical Oncology, National Center for Tumor Diseases (NCT), Heidelberg, Germany |
| 2016 – 2018 | Postdoctoral Researcher, German Cancer Research Center (DKFZ, “Applied Tumor Immunity”, PI: Prof. Dr. Dirk Jaeger) |
| 05/2016 | Medical license granted by the State of Baden-Wuerttemberg, Germany |
| 2013 - 2016 | Master of Science in Medical Physics at the Medical Faculty Mannheim of Heidelberg University |
| 2009 -2016 | Medical studies at the Medical Faculty Mannheim of Heidelberg University |
| CLINICAL TRAINING | |
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| 2021 | Board certification Internal Medicine |
| HONORS AND GRANTS | |
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| 2023 - 2024 | Transplant.KI, Gemeinsamer Bundesausschuss zur Förderung von Versorgungsforschung |
| 2022 - 2028 | Preventing early onset colorectal cancer (PEARL), BMBF |
| 2021 | German Award for Cancer Prevention, Young Investigator Category by the Manfred Lautenschläger Foundation and the German Cancer Research Center (DKFZ) |
| 2021 | Heinz Maier-Leibnitz Award by the German Research Foundation (DFG) and the German Federal Ministry of Education and Research (BMBF) |
| 2020 - 2022 | DEEP LIVER consortium, German Federal Ministry of Health (BMG), Germany |
| 2020- 2023 | Max-Eder-Grant of the German Cancer Aid (Deutsche Krebshilfe), Bonn, Germany |
| 2020 | Research Award for Colorectal Cancer Prevention (Stiftung Lebensblicke, Ludwigshafen, Germany) |
| 2020 | Research Award of the German Society for Medical Oncology (Arbeitsgemeinschaft Internistische Onkologie, AIO) |
| 2020 | Theodor-Frerichs-Award of the German Society for Internal Medicine (Deutsche Gesellschaft für Innere Medizin, DGIM) |
| 2019 - 2020 | START Grant of RWTH Aachen University, Aachen, Germany |
| 2017 - 2018 | NCT Heidelberg School of Oncology, Heidelberg, Germany |
| 2010 - 2016 | Various scholarships of Studienstiftung des Deutschen Volkes, German Research Council / SFB-TR23 „Vascular Differentiation and Remodeling“, Roche Pharma, Professional Society of German Physicians |
MEMBERSHIPS
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German Society for Visceral Medicine and Endocrinology (DGVS) #08969 |
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Member of the Academy of the Sciences and Arts of the State of North-Rhine-Westphalia, Germany with a supporting grant of 10,000 € p.a. |
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German Society of Internal Medicine (DGIM), #20985 |
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European Association for the Study of the Liver (EASL), #46505 |
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European Society for Medical Oncology (ESMO), #408721 |
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American Society of Clinical Oncology (ASCO), #6915052 |
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European Association for Cancer Research (EACR), #EACR26284 |
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Arbeitsgemeinschaft Internistische Onkologie (AIO) |
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Regular peer reviewer for: British Journal of Cancer, Clinical Cancer Research, Nature Medicine, Nature, Nature Comms, Nature Methods, Cancer Research. Full list at: https://publons.com/researcher/1307512/jakob-nikolas-kather/peer-review/ |
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Editorial board member in “ImmunoInformatics” (Elsevier) |
LINKS
Dr. Zunamys I. Carrero | Lab’s leadership team
Narmin Ghaffari Laleh, MSc | Research Scientist | Software Engineer
Oliver Lester Saldanha, MSc | Research Scientist |PhD Student
Didem Cifci, MSc | PhD Student
Hannah Sophie Muti | Physician Scientist
Chiara Löffler | Physician Scientist
Katherine Jane Hewitt, MD | PhD Student
Jan Niehues, PhD | Medical Student with a PhD in physics
Marko van Treeck, MSc | Research Software Engineer
Gregory Veldhuizen, MD, PhD | post-doctoral Physician Scientist
Xiaofeng Jiang, MD | PhD Student
Marco Gustav | Engineer and PhD Candidate
Omar el Nahhas, MSc | Computer Scientist and PhD Student
Emylou Matthaei, BSc | dental student
Lars Hilgers | medical student
Tobias Seibel | physics student
Tobias P. Seraphin | University Hospital Düsseldorf
Dr. med. Fiona Kolbinger | University Hospital Dresden
Selected publications
Check out Google Scholar or PubMed for a full list of publications. Below some recent publications are highlighted:
Saldanha OL, Quirke P, West NP, … Kather JN. Swarm learning for decentralized artificial intelligence in cancer histopathology. Nature Medicine (2022), doi: 10.1038/s41591-022-01768-5. Epub ahead of print.
Kather JN, Pearson AT, Halama N, … Luedde T. Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer, Nature Medicine (2019), doi: 10.1038/s41591-019-0462-y
Kather JN, Heij LR, Grabsch HI, … Luedde T. Pan-cancer image-based detection of clinically actionable genetic alterations, Nature Cancer (2020), doi: 10.1038/s43018-020-0087-6
Echle A, Grabsch HI, Quirke P, … Kather JN. Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning, Gastroenterology (2020), doi: 10.1053/j.gastro.2020.06.021
Kather JN, Calderaro J. Development of AI-based pathology biomarkers in gastrointestinal and liver cancer, Nature Reviews Gastroenterology and Hepatology (2020), doi: 10.1038/s41575-020-0343-3
Contact
© Anja Stübner
Clinical Artificial Intelligence
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