DDKI – Data-driven research at KI
Data-Driven research at KI is a university-wide initiative to promote data-driven research across the whole range of medical science and education practiced at KI. We define data-driven research broadly due to the use of large-scale and complex data, advanced analysis methods and extensive computational resources in the pursuit of addressing cutting-edge research questions.
Upcoming seminar
Register here before 5 September 2025
Date: 15 September 2025 at 13.00-14.00
Venue: Eva and Georg Klein, Biomedicum, Solnavägen 9, 171 65 Solna
Seminar topic
Building Bridges Between Data and Human Experience: Multimodal AI, Social Media, and the Future of Research, Publishing, and Collaboration.
Speaker
Dr. Yulin Hswen, Associate Professor of Epidemiology & Biostatistics at UCSF and UC Berkeley’s Computational Precision Health program
Funding calls
This call is part of the PALS initiative, supported by the Knut and Alice Wallenberg Foundation.
Apply here, application deadline: Sep 1, 2025 - 12:00 CET
Courses and external events
Courses:
- Applications of Machine Learning in Medicine Program (online, self-paced), Stanford School of Medicine, Stanford Center for Health Education
- Artificial Intelligence in Healthcare (online, self-paced), Stanford School of Medicine, Stanford Center for Health Education
- Evaluations of AI Applications in Healthcare (online, self-paced), Stanford School of Medicine, Stanford Center for Health Education
- AI in Healthcare Specialization (online, self-paced, 5-course series), Stanford School of Medicine, Stanford Center for Health Education
- Oxford Artificial Intelligence Programme (online, self-paced), Oxford University
- AI in Clinical Medicine (online live: 7-8 November 2024), Harvard University
- AI in Medicine Certificate (online, self-paced), University of Illinois Urbana-Champaign
- AI for Healthcare (online, live), Yong Loo Lin School of Medicine, Singapore, start date: 30.09.2024
- AI in Healthcare (Self-Paced with Live Instruction, 4-days), John Hopkins
- AI and digital transformation in healthcare (1 week course. 21-27 July 2024), University of Cambridge - Institute of Continuing Education, application deadline (23 June 2024)
- Artificial Intelligence in Healthcare (online), University of Central Lancashire; start date: September, January and May; duration 4 months
- Foundations of AI in Healthcare (online), The University of Melbourne
- AI in Medicine - Medical Imaging (In-person and virtually), University of Toronto, start date: 9 October 2024, running for 6 weeks
Other events:
- EITCA/AI ARTIFICIAL INTELLIGENCE ACADEMY (online), European Information Technologies Certification Academy, see the programme
- European Information Technologies Certification Institute
- Postgraduate Certificate: AI in Medicine (online), University of South Wales, application deadline: 7 March 2025
- Master's degree: Master’s Program in AI for Health (application period: (mid-October to mid-January), Stockholm University
- Master's Program: MSc Artificial Intelligence (AI) for Medicine & Medical Research, UCD Dublin - School of Medicine
Contact
Shireen Sindi
Senior Research SpecialistAdina Feldman
Scientific CoordinatorDDKI reference group
- Bionut - Carsten Daub
- CMB - Rickard Sandberg
- CNS - Klementy Shchetynsky
- Clinical Science and Education, Södersjukhuset - Thomas Olsson, thomas.a.olsson@regionstockholm.se
- CLINTEC - Fernando Seoane Martinez
- Clinical Sciences, Danderyd Hospital - Martin Magnéli
- DENTMED - Georgios Belibasakis, Ronaldo Lira Júnior
- GPH - Nicola Orsini
- LABMED - Ujjwal Neogi
- LIME - Carl Savage, Sabine Koch
- MBB - Jens Hjerling-Leffler, Eneritz Agirre
- MEB - Mark Clements, Sanela Kjellqvist
- MedH - Martin Cornillet
- MedS - Eduardo Villablanca, Pontus Naucler
- MTC - Oscar Bedoya Reina, Benjamin Murrell
- MMK - David Marlevi, Neda Rajamand Ekberg, Fatemah Rezayee
- NVS - Linus Jönsson, Axel Carlsson
- Neuro - Federico Iovino, Jan Mulder
- OnkPat - Linda Lindström, Martin Enge
- FyFa - Max Bell, Volker Lauschke
- KBH - Erdinc Sezgin, Andrea Merker
- IMM - Donghao Lu, Maria Feychting