Publications

David Nam, Julius Chapiro, Valerie Paradis, Tobias Paul Seraphin, und Jakob Nikolas Kather. Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: AI, Artificial CNN, Communications DICOM, Diagnosis; Digital HCC, Imaging Individual ML, MVI, Medicine; NAFLD, NASH, Prognosis Reporting TACE, TRIPOD, Transparent WSIs, a and artificial carcinoma; chemoembolisation; convolutional data deep diagnostic disease; fatty for hepatocellular images; imaging; in integration intelligence; invasion; learning; liver machine microvascular model multimodal multivariable network; neural non-alcoholic of or prediction slide steatohepatitis; support system; transarterial whole]

Roman C Maron, Achim Hekler, Sarah Haggenmüller, Christof von Kalle, Jochen S Utikal, Verena Müller, Maria Gaiser, Friedegund Meier, Sarah Hobelsberger, Frank F Gellrich, Mildred Sergon, Axel Hauschild, Lars E French, Lucie Heinzerling, Justin G Schlager, Kamran Ghoreschi, Max Schlaak, Franz J Hilke, Gabriela Poch, Sören Korsing, Carola Berking, Markus V Heppt, Michael Erdmann, Sebastian Haferkamp, Dirk Schadendorf, Wiebke Sondermann, Matthias Goebeler, Bastian Schilling, Jakob N Kather, Stefan Fröhling, Daniel B Lipka, Eva Krieghoff-Henning, und Titus J Brinker. Model soups improve performance of dermoscopic skin cancer classifiers. Eur. J. Cancer, (173):307--316, Elsevier BV, September 2022. [PUMA: Artificial Calibration; Deep Dermatology; Ensembles; Generalisation; Melanoma; Model Nevus; Robustness intelligence; learning; soups; topic_lifescience]

Jens Przybilla, Peter Ahnert, Holger Bogatsch, Frank Bloos, Frank M Brunkhorst, SepNet Critical Care Trials Group, Progress Study Group, Michael Bauer, Markus Loeffler, Martin Witzenrath, Norbert Suttorp, und Markus Scholz. Markov state modelling of disease courses and mortality risks of patients with community-acquired pneumonia. J. Clin. Med., (9)2:393, MDPI AG, Februar 2020. [PUMA: Markov SOFA community-acquired continuous-time decision making; medical model model; pneumonia; prognosis; score; sepsis; stochastic]

Jan Gaebel, Hans-Georg Wu, Alexander Oeser, Mario A Cypko, Matthaeus Stoehr, Andreas Dietz, Thomas Neumuth, Stefan Franke, und Steffen Oeltze-Jafra. Modeling and processing up-to-dateness of patient information in probabilistic therapy decision support. Artif. Intell. Med., (104)101842:101842, Elsevier BV, April 2020. [PUMA: Arden Decision Head Medical Therapy and decision delay; logic model modules; neck oncology; support syntax; system;]

Akshay Akshay, Masoud Abedi, Navid Shekarchizadeh, Fiona C Burkhard, Mitali Katoch, Alex Bigger-Allen, Rosalyn M Adam, Katia Monastyrskaya, und Ali Hashemi Gheinani. MLcps: machine learning cumulative performance score for classification problems. Gigascience, (12)Dezember 2022. [PUMA: Python classification evaluation evaluation; learning; machine model package; problems; score unified]

Najia Ahmadi, Michele Zoch, Patricia Kelbert, Richard Noll, Jannik Schaaf, Markus Wolfien, und Martin Sedlmayr. Methods used in the development of common data models for health data: Scoping review. JMIR Med. Inform., (11):e45116, August 2023. [PUMA: ; Data Development Healthcare Healthcare; Informatics Informatics; Interoperability Interoperability; Medical Observational Outcomes Partnership Partnership; Process Process; Repositories Repositories; Standardized Suggestive common data data; electronic elements elements; harmonisation harmonisation; health involvement model model; record record; stakeholder]