Diversity for AI in Medicine

The Center for Artificial Intelligence in Medicine (CAIM) promotes diversity and inclusion in AI research for healthcare. Its initiative DAIM (Diversity for AI in Medicine) was launched in May 2022 with a keynote lecture by a renowned medical robotics researcher. 

DAIM aims to promote diversity, equity and inclusion for the benefit of:

  • health and well-being of AI researchers with projects on healthcare applications (multi-perspective and inclusive workplace)
  • academic excellence and innovation through multiple viewpoints in AI research
  • fighting biases in AI development

DAIM encompasses activities in the areas of networking and public relations, mentoring, and research. Since its inception, the initiative has featured role models for successful careers in STEM and specifically AI research with a focus on medical applications. Ongoing research projects on bias and inclusion in AI development for medicine can apply for a dedicated DAIM award, which was first presented in November 2022.

Featured

Ana Leni Frei

Ana Leni Frei, Pathology, University of Bern

Ana Leni Frei does her PhD in computational pathology on cell interactions in rectal cancer. She hopes to help build AI tools that can assist pathologists to understand changes that occur in the tumor microenvironments of patients receiving neoadjuvant chemoradiotherapy and hopefully understand why 20% of them do not respond to the therapy.

Esther Brill

Esther Brill, Bern Psychiatry Services

Esther Brill is a PhD student in cognitive neuroscience at the University Hospital of Old Age Psychiatry and Psychotherapy Bern. As a digital native she considers connecting technology and clinical work essential to fight ever more prevalent neurodegenerative diseases such as dementia through computerized cognition games.

Charlotte Kern

Charlotte Kern / Verena Schöning, Inselspital

Charlotte Kern and Verena Schöning use different approaches such as data mining, machine learning, and modelling and simulation studies in pharmacometrics to predict the effects of medication on diseases and thus inform clinical decision making. During the COVID-19 pandemic, their research directly contributed to improved patient care.

Amith Kamath

Amith Kamath, ARTORG Center, Uni Bern

Amith Kamath wishes to facilitate faster radiotherapy treatment for patients with glioblastoma through AI-supported therapy planning. He looks forward to translating his PhD research at the Medical Image Analysis research group of the ARTORG Center into a clinical tool through the broad entrepreneurial support he is receiving in Bern.

Florence Aellen

Florence Aellen, Computer Science, Uni Bern

Florence Aellen is the deep learning specialist at the Cognitive Computational Neuroscience Lab of the Institute of Computer Science, University of Bern. For her PhD she works with a very interdisciplinary research team to unravel interrelations between electrical brain activity and states of consciousness.

Song Xue

Song Xue, Nuclear Medicine, Inselspital

Song Xue is a biomedical postdoctoral researcher specialized in deep learning at the Inselspital. Applying artificial intelligence to nuclear medicine, Song aims to reduce radiation in diagnostic PET imaging and to personalize dose prediction for radionuclide therapy.

Christoph Ammon

Christoph Ammon, Institute for Crimonology, Uni Bern

Christoph Ammon's dissertation deals with the increasingly intertwined relationship between humans and machines in the wake of recent developments in AI technology. He discusses how responsibility can be adequately attributed, especially in medical applications, and whether it would make sense to define an AI as a functional legal entity.

Negin Ghamsarian

Negin Ghamsarian, ARTORG Center, Uni Bern

Negin Ghamsarian is a postdoctoral researcher at the ARTORG Center for Biomedical Engineering Research. She believes that self-supervised and semi-supervised deep learning can overcome current constraints in the feasibility of AI techniques for surgical video analysis to better predict postoperative complications and offer more precise surgical interventions.

Katharina Wilmes

Katharina Wilmes, Department of Physiology, Uni Bern

Katharina Wilmes is fascinated by the question how humans learn in an uncertain world. To find out, she is developing special neuroscientific models at the Institute of Physiology at the University of Bern.

DAIM Events

SAVE THE DATE!
7 March 2024 Awareness Raising Symposium - Unconsious Biases "Avoiding Bias in AI: Combating Inequality in Data, Gender and Socioeconomics" - learn more
26 June 2023 Dr. Lisa Falco, Lead Consultant AI & Data at Zühlke  Lunch Talk "Responsible AI: The Key to Ethical, Safe and Inclusive Software Development" - learn more
8 March 2023 Entrepreneurial Workshop - Female MedTech Entrepreneurs "AI MedTech Founders": How to translate your research into a startup - learn more
24 November 2022 CAIM Symposium 2022 DAIM award for inclusive AI in healthcare research - learn more
18 October 2022 Dr. Lisa Koch, Institute for Ophthalmic Research, University of Tübingen  Lunch Talk "Towards Save and Effective Medical Image Analysis Systems" - learn more
13 May 2022 Prof. Franziska Mathis-Ullrich, Karlsruhe Institute of Technology
Lunch Talk "Cognition-Guided Robotics and Embedded AI for Surgeons" - learn more

Join our community!

DAIM community (June 2023)

To join the initiative for Diversity for AI in Medicine (DAIM), please sign up here:

Become a member of DAIM


Celebrating 1 Year of DAIM with our growing community.
Thank you for your support and see you soon!

Who we are

DAIM is composed of Equality representatives from our Center, partnered with equal opportunities entities at the University of Bern and the Medical Faculty. This includes CAIM's outreach activities entities and a representative from the Ethics Lab.

For all questions on DAIM, feel free to contact info.caim@unibe.ch

DAIM Committee (from left): Mauricio Reyes, Initiator | Inti Zlobec, Mentoring | Stavroula Mougiakakou, Research and Teaching | Rouven Porz, Ethics | Monika Kugemann, Communications (© CAIM, University of Bern)