gms | German Medical Science

Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH)

08.09. - 13.09.2024, Dresden

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A Concept for Mining Transitive Sequential Patterns from Pancreatic Cancer Patient Journeys

Meeting Abstract

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  • Jonas Hügel - University Medical Center Göttingen, Department of Medical Informatics, Göttingen, Germany; University of Göttingen, Campus Intstitute Data Science, Göttingen, Germany
  • Janosch Schneider - University Medical Center Göttingen, Department of Medical Informatics, Göttingen, Germany
  • Daniel Tran Ortega - University Medical Center Göttingen, Department of Medical Informatics, Göttingen, Germany
  • Ella Maria Jentsch - University Medical Center Göttingen, Department of Medical Informatics, Göttingen, Germany
  • Sophia Rheinländer - University Medical Center Göttingen, Department of Medical Informatics, Göttingen, Germany
  • Nils Beyer - University Medical Center Göttingen, Department of Medical Informatics, Göttingen, Germany
  • Hossein Estiri - Clinical Augmented Intelligence Group, Massachusetts General Hospital, Boston, United States; Harvard Medical School, Boston, United States
  • Christoph Ammer-Herrmenau - University Medical Center Göttingen, Clinic for Gastroenterology, Gastrointestinal Oncology and Endocrinology, Göttingen, Germany
  • Elisabeth Hessmann - University Medical Center Göttingen, Clinic for Gastroenterology, Gastrointestinal Oncology and Endocrinology, Göttingen, Germany
  • Alexander Otto König - University Medical Center Göttingen, Clinic for Gastroenterology, Gastrointestinal Oncology and Endocrinology, Göttingen, Germany
  • Volker Ellenrieder - University Medical Center Göttingen, Clinic for Gastroenterology, Gastrointestinal Oncology and Endocrinology, Göttingen, Germany
  • Ulrich Sax - University Medical Center Göttingen, Department of Medical Informatics, Göttingen, Germany; University of Göttingen, Campus Intstitute Data Science, Göttingen, Germany
  • Clinical Research Unit 5002 (CRU 5002) - University Medical Center Göttingen, Göttingen, Germany

Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH). Dresden, 08.-13.09.2024. Düsseldorf: German Medical Science GMS Publishing House; 2024. DocAbstr. 667

doi: 10.3205/24gmds107, urn:nbn:de:0183-24gmds1071

Veröffentlicht: 6. September 2024

© 2024 Hügel et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.

Gliederung

Text

Pancreatic cancer, renowned for its aggressive nature and poor prognosis, necessitates the optimization of treatment strategies. The sequence of procedures in clinical trials is critical, such as evaluating the potential benefits of preoperative chemo-radio-therapy for pancreatic cancer. Nevertheless, we might not be aware of other temporal sequences which have an effect on therapy response or the general outcome. Extracting transitive sequential patterns from patients' medical trajectories allows researchers to identify temporal characteristics for complex diseases. We illustrate how such sequential patterns can be discovered and might be utilized in pancreatic cancer research as well as patient care.

The authors declare that they have no competing interests.

The authors declare that a positive ethics committee vote has been obtained.