Theresa Willem M.A.

Research associate

Theresa Willem is a research associate at the Institute for the History and Ethics of Medicine and a doctoral candidate at the interface between our institute and the Department of Science, Technology, and Society (STS) of the School of Social Sciences and Technology at TUM.

Theresa studied Media Science (M.A.) at the University of Regensburg, at IHECS (Brussels) and at the Humboldt University of Berlin and gained practical experience in digital health innovation and development in the Berlin startup sector.

From 03/2020-02/2023 she was part of the research project TherVacB (50%). Her research focused on ethical, social and regulatory issues of patient recruitment for clinical trials via social networks.

From 01/2021-12/2023 she was part of the research project DR-AI (50%). Her research focused on the ethical and social implications of the development of diagnosis-supporting AI systems for radiology and dermatology, as well as the integration of ethical research into technology projects.

Since 03/2023 Theresa is employed as AI Ethics Consultant at Helmholtz AI (Helmholtz Munich) and since 01/2024 she is the Lab Manager of the Munich Embedded Ethics Lab here at TUM.

Theresa Willem is a PhD student working at the intersection of artificial intelligence, digital health, ethics and social science. Her research focuses on ethical and social issues in the research and development of machine learning healthcare applications, particularly in the field of imaging techniques.

Theresa is an alumna of the Bavarian Elite Academy and the German National Academic Foundation.

  • Ethical implications of modern biomedicine and health technology.
  • Research Ethics
  • Embedded Ethics
  • Science and Technology Studies (STS)
2024
Wollek, Alessandro;Willem, Theresa;Ingrisch, Michael;Sabel, Bastian;Lasser, Tobias (2024). Out-of-distribution detection with in-distribution voting using the medical example of chest x-ray classification., Band 51, Ausgabe 4, S. 2721-2732 [mehr...]
2023
Cheslerean-Boghiu, Theodor;Fleischmann, Melia-Evelina;Willem, Theresa;Lasser, Tobias (2023). Transformer-based interpretable multi-modal data fusion for skin lesion classification, arXiv [mehr...]
Goldman, Nina;Willem, Theresa;Buyx, Alena;Zimmermann, Bettina M (2023). Practical Benefits, Challenges, and Recommendations on Social Media Recruitment: Multi-Stakeholder Interview Study., Band 25 [mehr...]
Mühlhoff, Rainer;Willem, Theresa (2023). Social media advertising for clinical studies: Ethical and data protection implications of online targeting, SAGE Publications, In: Big Data & Society, Band 10, Ausgabe 1, S. 205395172311561 [mehr...]
Wollek, Alessandro;Graf, Robert;Čečatka, Saša;Fink, Nicola;Willem, Theresa;Sabel, Bastian O;Lasser, Tobias (2023). Attention-based Saliency Maps Improve Interpretability of Pneumothorax Classification., Band 5, Ausgabe 2 [mehr...]
2022
Willem, T;Krammer, S;Böhm, A-S;French, L E;Hartmann, D;Lasser, T;Buyx, A (2022). Risks and benefits of dermatological machine learning health care applications-an overview and ethical analysis., Band 36, Ausgabe 9, S. 1660-1668 [mehr...]
Wollek, Alessandro;Willem, Theresa;Ingrisch, Michael;Sabel, Bastian;Lasser, Tobias (2022). A knee cannot have lung disease: out-of-distribution detection with in-distribution voting using the medical example of chest X-ray classification, arXiv [mehr...]
Zimmermann, Bettina M;Willem, Theresa;Bredthauer, Carl Justus;Buyx, Alena (2022). Correction: Ethical Issues in Social Media Recruitment for Clinical Studies: Ethical Analysis and Framework., Band 24, Ausgabe 9 [mehr...]
Zimmermann, Bettina M;Willem, Theresa;Bredthauer, Carl Justus;Buyx, Alena (2022). Ethical Issues in Social Media Recruitment for Clinical Studies: Ethical Analysis and Framework., Band 24, Ausgabe 5 [mehr...]
  • Ethics and Palliative Care Seminar (Certificate of Achievement GTE) (SoSe and WiSe)

Theresa Willem gives scientific and public lectures on the following topics:

  • Ethical challenges in medicine
  • Ethical implications of new developments and technologies in medicine (AI in medicine).
en_USEN