Brodbeck, Dominique
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Brodbeck, Dominique
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- PublikationSolving the explainable AI conundrum by bridging clinicians’ needs and developers’ goals(Nature, 22.05.2023) Bienefeld, Nadine; Boss, Jens Michael; Lüthy, Rahel; Brodbeck, Dominique; Azzati, Jan; Blaser, Mirco; Willms, Jan; Keller, Emanuela [in: npj Digital Medicine]Explainable artificial intelligence (XAI) has emerged as a promising solution for addressing the implementation challenges of AI/ML in healthcare. However, little is known about how developers and clinicians interpret XAI and what conflicting goals and requirements they may have. This paper presents the findings of a longitudinal multi-method study involving 112 developers and clinicians co-designing an XAI solution for a clinical decision support system. Our study identifies three key differences between developer and clinician mental models of XAI, including opposing goals (model interpretability vs. clinical plausibility), different sources of truth (data vs. patient), and the role of exploring new vs. exploiting old knowledge. Based on our findings, we propose design solutions that can help address the XAI conundrum in healthcare, including the use of causal inference models, personalized explanations, and ambidexterity between exploration and exploitation mindsets. Our study highlights the importance of considering the perspectives of both developers and clinicians in the design of XAI systems and provides practical recommendations for improving the effectiveness and usability of XAI in healthcare.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationRWD-Cockpit. Application for quality assessment of real-world data(JMIR Publications, 18.10.2022) Degen, Markus; Babrak, Lmar; Smakaj, Erand; Agac, Teyfik; Asprion, Petra; Grimberg, Frank; Van der Werf, Daan; Van Ginkel, Erwin Willem; Tosoni, Deniz David; Clay, Ieuan; Brodbeck, Dominique; Natali, Eriberto; Schkommodau, Erik; Miho, Enkelejda [in: JMIR Formative Research]Digital technologies are transforming the health care system. A large part of information is generated as real-world data (RWD). Data from electronic health records and digital biomarkers have the potential to reveal associations between the benefits and adverse events of medicines, establish new patient-stratification principles, expose unknown disease correlations, and inform on preventive measures. The impact for health care payers and providers, the biopharmaceutical industry, and governments is massive in terms of health outcomes, quality of care, and cost. However, a framework to assess the preliminary quality of RWD is missing, thus hindering the conduct of population-based observational studies to support regulatory decision-making and real-world evidence.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationCloud-based three-dimensional pattern analysis and classification of proximal humeral fractures – A feasibility study(EasyChair, 2022) Kalt, Denise; Gerber Popp, Ariane; Degen, Markus; Brodbeck, Dominique; Coigny, Florian; Suter, Thomas; Schkommodau, Erik; Rodriguez y Baena, Ferdinando; Giles, Joshua W.; Stindel, Eric [in: Proceedings of the 20th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery]For the complex clinical issue of treatment decision for proximal humeral fractures, dedicated software based on three-dimensional (3D) computer tomography (CT) models would potentially allow for a more accurate fracture classification and help to plan the surgical strategy needed to reduce the fracture in the operating theatre. The aim of this study was to elaborate the feasibility of implementation of such software using state-of-the-art cloud technology to enable access to its functionalities in a distributed manner. Feasibility was studied by implementation of a prototype application, which was tested in a usability study with five biomedical engineers. Implementation of a cloud-based solution was feasible using state-of-the-art technology under application of a specific software architectural approach allowing to distribute computational load between client and server. Mean System Usability Scale (SUS) Score for the developed application was determined to be 63 (StDev 20.4). These results can be interpreted as a medium low usability with high standard deviation of the measured SUS score. We conclude that more test subjects should be included in future studies and the developed application should be evaluated with a representative user group such as orthopaedic shoulder surgeons in a clinical setting.04B - Beitrag Konferenzschrift
- PublikationAugmented feedback system to support physical therapy of non-specific low back pain(Springer, 2010) Brodbeck, Dominique; Degen, Markus; Stanimirov, Michael; Kool, Jan; Scheermesser, Mandy; Oesch, Peter; Neuhaus, Cornelia; Fred, Ana; Filipe, Joaquim; Gamboa, Hugo [in: Biomedical Engineering Systems and Technologies]Low back pain is an important problem in industrialized countries. Two key factors limit the effectiveness of physiotherapy: low compliance of patients with repetitive movement exercises, and inadequate awareness of patients of their own posture. The Backtrainer system addresses these problems by real-time monitoring of the spine position, by providing a framework for most common physiotherapy exercises for the low back, and by providing feedback to patients in a motivating way. A minimal sensor configuration was identified as two inertial sensors that measure the orientation of the lower back at two points with three degrees of freedom. The software was designed as a flexible platform to experiment with different hardware, and with various feedback modalities. Basic exercises for two types of movements are provided: mobilizing and stabilizing. We developed visual feedback - abstract as well as in the form of a virtual reality game - and complemented the on-screen graphics with an ambient feedback device. The system was evaluated during five weeks in a rehabilitation clinic with 26 patients and 15 physiotherapists. Subjective satisfaction of subjects was good, and we interpret the results as encouraging indication for the adoption of such a therapy support system by both patients and therapists.04B - Beitrag Konferenzschrift
- PublikationBacktrainer. Computer-aided therapy system with augmented feedback for the lower back(SciTePress, 2009) Brodbeck, Dominique; Degen, Markus; Stanimirov, Michael; Kool, Jan; Scheermesser, Mandy; Oesch, Peter; Neuhaus, Cornelia; Azevedo, Luis; Londral, Ana [in: Proceedings of the International Conference on Health Informatics BIOSTEC]Low back pain is an important problem in industrialized countries. Two key factors limit the effectiveness of physiotherapy: low compliance of patients with repetitive movement exercises, and inadequate awareness of patients of their own posture. The Backtrainer system addresses these problems by real-time monitoring of the spine position, by providing a framework for most common physiotherapy exercises for the low back, and by providing feedback to patients in a motivating way. A minimal sensor configuration was identified as two inertial sensors that measure the orientation of the lower back at two points with three degrees of freedom. The software was designed as a flexible platform to experiment with different hardware, and with various feedback modalities. Basic exercises for two types of movements are provided: mobilizing and stabilizing. We developed visual feedback - abstract as well as in the form of a virtual reality game - and complemented the on-screen graphics with an ambient feedback device. The system was evaluated during five weeks in a rehabilitation clinic with 26 patients and 15 physiotherapists. Subjective satisfaction of subjects was good, and we interpret the results as encouraging indication for the adoption of such a therapy support system by both patients and therapists.04B - Beitrag Konferenzschrift