AI in clinical diagnostics: challenges and opportunities

Activity: Talks and presentationsConference presentations

Description

International Workshop Baltic-Sea-Health-Region-Meeting | Hybrid | 90 min"AI in clinical diagnostics: challenges and opportunities"The Baltic Sea Region is known as the leader in digital health in Europe. The application of Artificial Intelligence (AI) in Medicine is one of the most promising developments in this decade.Today AI-based diagnostics is battling challenges and barriers in the healthcare environment: Under- standing the mismatch between clinical needs and industry services and products, the need for a bet- ter model of development, cooperation with industry, implementation and adoption of AI solutions, data handling and privacy concerns can impact the development and slow down the process.This session aims to give a practical view of AI in healthcare and the challenges faced in implementing it. After a general introduction to the ethical challenges related to AI and using AI in clinical practice, ex- amples from a technology development and clinical perspective are presented. The session will close with a round table discussion including the audience.Moderation: Dr. Jaanus Pikani, President, ScanBalt MTÜ, Tartu/EstoniaSpeakers: Prof. Dr. Barry O’Sullivan, Fellow AAAI, EurAI, MRIA, Director, Insight SFI Research Centre forData Analytics & SFI Centre for Research Training in AI, University College Cork, Ireland  Maria Bach Nielsen, Project Manager, Cerebriu A/S, Copenhagen, Denmark Prof. Dr. Petra Svedberg, Professor of Nursing, Halmstad University, Sweden

Titel for presentation: Enhancing AI Adoption in Radiology Clinics: A Participatory and Techno- Anthropological Perspective

Abstract: The potential of Artificial Intelligence (AI) in healthcare, especially within radiology, holds promise for improved clinical outcomes and workflow optimization. Yet, the transformation of this potential into efficient clinical practice remains a substantial and resource-demanding challenge. Recent discourse within implemen- tation science often fixates on disrupting or radically altering workflows to accommodate decision-support tech- nologies. However, our experience from numerous live test implementations, co-creative efforts, and ongoing observation studies of clinical workflows suggests a different, more context-sensitive and incremental ap- proach to ensure both social and technical innovation. In 2022, we embarked on a techno-anthropological pro- ject aimed at establishing an optimal process model for AI adoption in radiology clinics. This project places considerable emphasis on incorporating healthcare professionals' perspectives through qualitative methodolo- gies, thus creating a comprehensive five-stage adaption process model. This model enables early assessment of added value before committing to large-scale retrospective and or prospective validation.The process model incorporates baseline setting for workflow and praxis, mapping of organizational and tech- nological ecosystem structures, identification of workflow pain points, initiation and preparation for implementa- tion with technical and clinical staff. We also monitor the implementation process and assess adoption efforts. This research, being conducted across select hospitals in Denmark and the United States, focuses on the AI implementation of Cerebriu Apollo in Brain MRI workflows. The presentation seeks to share the insights gained, challenges faced, and opportunities identified from previous and ongoing implementation projects.
Period7 Jun 2023
Event title18th National Conference on Health Economy 2023
Event typeConference
LocationRostock, Germany, Mecklenburg-VorpommernShow on map
Degree of RecognitionInternational