Vier Beiträge auf der Hawaii International Conference on System Sciences (HICSS) 2021 angenommen
Auf der 54. Hawaii International Conference on System Sciences (HICSS), die vom 5. - 8. Januar 2021 stattfindet, wurden vier Konferenzbeiträge der Forschungsgruppe cii angenommen.
What Your Radiologist Might Be Missing: Using Machine Learning to Identify Mislabeled Instances of X-ray Images
Autoren: Tim Rädsch, Sven Eckhardt, Florian Leiser, Konstantin Pandl, Scott Thiebes, Ali Sunyaev
Abstract: Label quality is an important and common problem in contemporary supervised machine learning research. Mislabeled instances in a data set might not only impact the performance of machine learning models negatively, but also make it more difficult to explain, and thus trust, the predictions of those models. While extant research has especially focused on the ex-ante improvement of label quality by proposing improvements to the labeling process, more recent research has started to investigate the use of machine learning-based approaches to automatically identify mislabeled instances in training data sets. In this study, we propose a two-staged pipeline for the automatic detection of potentially mislabeled instances in a large medical data set. Our results show that our pipeline successfully detects mislabeled instances, helping us to identify 7.4% of mislabeled instances of Cardiomegaly in the data set. With our research, we contribute to ongoing efforts regarding data quality in machine learning.
Online at Will: A Novel Protocol for Mutual Authentication in Peer-to-Peer Networks for Patient-Centered Health Care Information Systems
Autoren: Imrana Abdullahi Yari, Tobias Dehling, Felix Kluge, Bjoern Eskofier, Ali Sunyaev
Abstract: Patient-centered health care information systems (PHSs) on peer-to-peer (P2P) networks promise decentralization benefits. P2P PHSs, such as decentralized personal health records or interoperable Covid-19 proximity trackers, can enhance data sovereignty and resilience to single points of failure, but the openness of P2P networks introduces new security issues. We propose a novel, simple, and secure mutual authentication protocol that supports offline access, leverages independent and stateless encryption ser-vices, and enables patients and medical professionals to establish secure connections when using P2P PHSs. Our protocol includes a virtual smart card (software-based) feature to ease integration of authentication features of emerging national health-IT infrastructures. The security evaluation shows that our protocol resists most online and offline threats while exhibiting performance comparable to traditional, albeit less secure, password-based authentication methods. Our protocol serves as foundation for the design and implementation of P2P PHSs that will make use of P2P PHSs more secure and trustworthy.
Hier lesen Sie den Beitrag auf ResearchGate
Drivers and Inhibitors for Organizations’ Intention to Adopt Artificial Intelligence as a Service
Autoren: Konstantin Pandl, Heiner Teigeler, Sebastian Lins, Scott Thiebes, Ali Sunyaev
Abstract: The adoption of artificial intelligence promises tremendous economic benefits for organizations. Yet, many organizations struggle to unlock the full potential of this technology. To ease the adoption of artificial intelligence for organizations, several cloud providers have begun offering artificial intelligence as a service (AIaaS). Extant research on AIaaS exhibits a strong focus on technical aspects and has opposing views on what drives or inhibits the adoption of AIaaS within organizations. In this research, we synthesize extant research on AIaaS adoption factors and conduct semi-structured interviews with practitioners. Our research yields 12 factors that drive and 13 factors that inhibit the adoption of AIaaS in practice. We thereby close a gap in scholarly knowledge on the adoption of this emerging service technology, especially on inhibiting factors, and help to guide future research on related behavioral and technical aspects.
Are Gamification Projects Different? An Exploratory Study on Software Project Risks for Gamified Health Behavior Change Support Systems
Autoren: Simon Warsinsky, Manuel Schmidt-Kraepelin, Scott Thiebes, Ali Sunyaev
Abstract: Gamification is increasingly utilized in information systems to afford positive experiences that are typically perceived from playing games. Despite potential benefits, gamification projects have shown to be prone for failure which may lead to severe harmful effects for its users. In traditional software projects, project managers try to mitigate failure through project risk management. However, gamification projects bring with them several differences in comparison to traditional software projects and it is unclear how extant knowledge may be transferred. We address this issue by conducting ten semi-structured interviews with experts involved in the development of gamified health behavior change support systems. Our results indicate that gamification has substantial impacts on various risk factors. We contribute to gamification and project management literature as we are among the first who conceptualize gamification projects as special software projects with different project risk factors.
Hier lesen Sie den Beitrag auf ResearchGate
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Aus der Forschungsgruppe Critical Information Infrastructures