Bremen Big Data Challenge

Fraunhofer MEVIS participates in the pupils track of the Bremen Big Data Challenge. Teams of up to three pupils explore the respective topic and become creative problem solvers. During the exploration phase they will be guided by their teacher and researchers from Fraunhofer MEVIS. The results can be used as “Facharbeit” or “Klausurersatzleistung”.

The pupil's challenge was initiated by the Stiftung Bremer Wertpapierbörse (BWB) to foster the cooperation of science and schools. The aim of the challenges is to break with the classical teaching subjects and formats and to bring the teaching contents close to the participating research institutes.
 

2025

At Fraunhofer MEVIS, researchers, clinicians, and industry partners are collaborating to develop software solutions that help healthcare professionals manage the rapidly increasing complexity of their work. The processing of medical data using artificial intelligence plays a key role in this effort. As part of the BBDC 2025, the goal will therefore be to train an artificial intelligence (AI) system that supports pathologists in evaluating bone marrow smears more quickly and objectively through automation. Specifically, these analyses play a crucial role in the diagnosis of leukemia. Understanding what these bone marrow smears look like and how to handle this data is a key part of training an AI and this year’s challenge. You will explore what an AI for analyzing bone marrow smears might look like, how to train it, how accurate the resulting predictions are, and what limitations exist in the automated analysis of bone marrow smears using AI.

Challenge 2025 by Farina Kock, Daniela Schacherer, Anna Rörich

For Whom?	When?	Further Information / Application
Pupils visiting classes 11–13	September 2025 – January 2026	Analysis of bone marrow smears Hemato-Oncology Application

 

2024

At Fraunhofer MEVIS, researchers, clinicians, and industry partners are collaborating to develop software solutions that help healthcare professionals manage the rapidly increasing complexity of their work. The processing of medical data using artificial intelligence plays a key role in this effort. As part of the BBDC 2024, the focus will therefore be on training an artificial intelligence system that supports physicians in making better use of existing clinical data and deriving the best possible treatment method for their patients. Specifically, the focus will be on predicting complications, such as chronic heart failure, following a heart attack using an AI method—decision trees. You will investigate what a decision tree for predicting complications following a heart attack might look like, how to generate it automatically, how accurate the resulting predictions are, and what limitations exist for this form of AI.

Challenge 2024 by Rieke Alpers and Anna Rörich

For Whom?	When?	Further Information / Application
Pupils visiting classes 11–13	September 2024 – January 2025	Clinical decision support for physicians Application