Designing Visual Markers for Continuous Artificial Intelligence Support

Colonoscopy, the visual inspection of the large bowel using an endoscope, offers protection against colorectal cancer by allowing for the detection and removal of pre-cancerous polyps. The literature on polyp detection shows widely varying miss rates among clinicians, with averages ranging around 22%--27%. While recent work has considered the use of AI support systems for polyp detection, how to visualise and integrate these systems into clinical practice is an open question. In this work, we explore the design of visual markers as used in an AI support system for colonoscopy. Supported by the gastroenterologists in our team, we designed seven unique visual markers and rendered them on real-life patient video footage. Through an online survey targeting relevant clinical staff (N = 36), we evaluated these designs and obtained initial insights and understanding into the way in which clinical staff envision AI to integrate in their daily work-environment. Our results provide concrete recommendations for the future deployment of AI support systems in continuous, adaptive scenarios

Classification of Polarimetric SAR Data Using Dictionary Learning

End-user development (EUD) research has yielded a variety of novel environments and techniques, often accompanied by lab-based usability studies that test their effectiveness in the completion of representative real-world tasks. While lab studies play an important role in resolving frustrations and demonstrating the potential of novel tools, they are insufficient to accurately determine the acceptance of a technology in its intended context of use, which is highly dependent on the diverse and dynamic requirements of its users, as we show here. As such, usability in the lab is unlikely to represent usability in the field. To demonstrate this, we first describe the results of a think-aloud usability study of our EUD tool “Jeeves”, followed by two case studies where Jeeves was used by psychologists in their work practices. Common issues in the artificial setting were seldom encountered in the real context of use, which instead unearthed new usability issues through unanticipated user needs. We conclude with considerations for usability evaluation of EUD tools that enable development of software for other users, including planning for collaborative activities, supporting developers to evaluate their own tools, and incorporating longitudinal methods of evaluation.Postprin

Heterogeneous stectrum of mutations in the Fanconi anaemia group A gene

31nonenoneWIJKER M; MORGAN NV; HERTERICH S; VAN BERKEL CGM; TIPPING AJ; SCHNDLER D; GILLE JJP; PALS G; SAVINO M; ALTAY C; MOHAN SP; DOKAL I; CAVENAGH J; MARSH J; VAN WEEL M; ORTEGA JJ; SCULER D; SAMOCHATOVA E; KARWACKI M; BERKASSY A; ABECASIS M; EBELL W; KWEE ML; GIBSON RA; GLUCKMAN E; ARWERT F; JOENJE H; SAVOIA A.; HOEHN H; PRONK JC; MATHEW CGWijker, M; Morgan, Nv; Herterich, S; VAN BERKEL, Cgm; Tipping, Aj; Schndler, D; Gille, Jjp; Pals, G; Savino, M; Altay, C; Mohan, Sp; Dokal, I; Cavenagh, J; Marsh, J; VAN WEEL, M; Ortega, Jj; Sculer, D; Samochatova, E; Karwacki, M; Berkassy, A; Abecasis, M; Ebell, W; Kwee, Ml; Gibson, Ra; Gluckman, E; Arwert, F; Joenje, H; Savoia, Anna; Hoehn, H; Pronk, Jc; Mathew, C