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ADBoard | Therapeutic Assist and Decision Algorithms for Hepatobiliary Tumor Boards
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The Gemeinsamer Bundesausschuss (Federal Joint Committee, G-BA) will fund a new collaborative project of the Charité's Dept. of Surgery and the Deutsches Forschungszentrum für Künstliche Intelligenz (German Research Center for Artificial Intelligence, DFKI), Speech and Language Technology.

The aim of the project Therapeutic Assist and Decision Algorithms for Hepatobiliary Tumor Boards (ADBoard) is the validation and evaluation of decision support systems based on linguistic and semantic methods of artificial intelligence (AI) for interdisciplinary tumour conferences in the care of tumour patients. Natural language processing (NLP) and machine learning (ML) will provide the technical basis for data extraction, data filtration and decision support for the automated generation of therapy recommendations. Interdisciplinary tumour board conferences are medical conferences, usually held on a weekly basis, which are required by the respective medical societies to determine a therapy or monitoring plan for patients with malignant diseases. Participants are representatives of the required medical disciplines who, taking into account the tumour characteristics and the general health of the patient, review the treatment options and make a therapy recommendation.

The Gemeinsamer Budesausschuss (Federal Joint Committee, G-BA) has the mandate to promote new forms of health care that go beyond the current standard provision of statutory health insurance, and health care research projects that are aimed at gaining knowledge to improve existing health care.

ADBoard is a collaboration of Priv.-Doz. Dr. Felix Krenzien, Priv.-Doz. Dr. Christian Benzing, Prof. Dr. Dominik Modest, Prof. Dr. Johann Pratschke (Charité – Universitätsmedizin Berlin) and Prof. Dr.-Ing. Sebastian Möller, Head of Research Department Speech and Language Technology, German Research Center for Artificial Intelligence.
CASSANDRA | Clinical ASSist AND aleRt Algorithms
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The Innovationsausschuss beim Gemeinsamen Bundesausschuss (G-BA) is funding 33 new projects in healthcare research. A total of 186 project applications were received in response to the funding announcements of December 2019. Nine project proposals from the open topic area and 24 project proposals from the topic-specific area received a positive funding decision.

Our project CASSANDRA (Clinical ASSist AND aleRt Algorithms – Early detection of postoperative complications with machine learning algorithms) is one of the projects funded for three years.

The aim of the project is to evaluate Machine Learning (ML) in the detection of postoperative complications after major abdominal surgery. By means of digital records and ML-driven analysis of perioperative risk factors, postoperative parameters as well as telemedical vital parameter monitoring, it is to be examined whether complications requiring treatment – in particular infections of the abdominal cavity after liver, pancreas, stomach and intestinal surgery – can be automatically detected and predicted, in order to develop the basis for an autonomous real-time monitoring system on normal wards.
CASSANDRA is a collaboration of Axel Winter, Dr. Max Maurer, Prof. Dr. Igor M. Sauer (Charité – Universitätsmedizin Berlin) and Prof. Dr. Bert Arnrich, Head of the Chair, Professor for Digital Health - Connected Healthcare, Hasso Plattner Institut.
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