DigiHealth-AI: Outcomes of the First Blended Intensive Programme (BIP) on AI for Health – a Cross-Disciplinary Multi-Institutional Short Teaching Course

Main Article Content

Tosin Adewumi https://orcid.org/0000-0002-5582-2031
Martin Gerdes https://orcid.org/0000-0003-4408-5838
Georgi Chaltikyan https://orcid.org/0000-0003-0743-2036
Fara Fernandes https://orcid.org/0000-0002-8522-5166
Lars Lindsköld https://orcid.org/0009-0002-1399-8589
Marcus Liwicki
Michelle Catta-Preta https://orcid.org/0009-0006-9200-1976

Keywords

machine learning, healthcare, pedagogy

Abstract

We reflect on the experiences in organizing and implementing a high-quality Blended Intensive Programme (BIP) as a joint international event. A BIP is a short programme that combines physical mobility with a virtual part. The 6-day event, titled “DigiHealth-AI: Practice, Research, Ethics, and Regulation”, was organized in collaboration with partners from five European nations and support from the EU’s ERASMUS+ programme in November 2023. We introduced a new learning method called ProCoT, involving large language models (LLMs), for preventing cheating by students in writing. We designed an online survey of key questions, which was conducted at the beginning and the end of the BIP. The highlights of the survey are as follows: By the end of the BIP, 84% of the respondents agreed that the intended learning outcomes (ILOs) were fulfilled, 100% strongly agreed that artificial intelligence (AI) benefits the healthcare sector, 62% disagree that they are concerned about AI potentially eliminating jobs in the healthcare sector (compared to 57% initially), 60% were concerned about their privacy when using AI, and 56% could identify, at least, two known sources of bias in AI systems (compared to only 43% prior to the BIP). A total of 541 votes were cast by 40 students, who were the respondents. The minimum and maximum numbers of students who answered any particular survey question at a given period are 25 and 40, respectively.

Abstract 15 | DigiHealth-AI Downloads 14

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