TY - CHAP A1 - Appenzeller, Arno A1 - Bartholomäus, Sebastian A1 - Breitschwerdt, Rüdiger A1 - Claussen, Carsten A1 - Geisler, Sandra A1 - Hartz, Tobias A1 - Kachel, Philipp A1 - Krempel, Erik A1 - Robert, Sebastian A1 - Ruth Zeissig, Sylke T1 - Towards Distributed Healthcare Systems – Virtual Data Pooling Between Cancer Registries as Backbone of Care and Research T2 - 2021 IEEE/ACS 18th International Conference on Computer Systems and Applications (AICCSA) N2 - German cancer registries offer a systematic approach for the collection, storage, and management of data on patients with cancer and related diseases. Much hope in research and healthcare in general is depending on such register-based analyses in order to comprehensively consider the features of a highly diverse population. Next to the data collection the cancer registries are responsible for data protection. To fulfill legal regulations, access to data has to be controlled in a strict way leading to sometimes bureaucratic and slow processes. The situation is especially complicated in Germany, since cancer data is distributed over numerous federal cancer registries. If a nationwide data evaluation is conducted a research team has to negotiate a separate contract with each cancer registry.In a joint work in progress effort of cancer registries, technical, medical, and economical experts we propose a different solution for cooperative data processing. Our approach aims for combining data in a virtual pool based on the selection criteria of individual requests from researchers. To achieve our goal, we adapt the Fraunhofer Medical Data Space as enabling technology. The architecture we propose will allow us to pool data of multiple partners regulated by data access policies. In doing so, each of the data sources can introduce its own rules and specifications on how data is used. Additionally, we add a digital consent management that will allow individual patients to decide how their data is used. Finally, we show the high potential of the cooperative analysis of distributed cancer data supported by the proposed solution in our approach. KW - Systematics KW - Space technology KW - Soft sensors KW - Sociology KW - Distributed databases KW - Process control KW - Medical services Y1 - 2021 UR - https://doi.org/10.1109/AICCSA53542.2021.9686918 SP - 1 EP - 8 ER - TY - CHAP A1 - Philipp, Patrick A1 - Becker, Silvia A1 - Robert, Sebastian A1 - Hempel, Dirk A1 - Beyerer, Jürgen T1 - Modeling of Medical Treatment Processes for an Interactive Assistance Based on the Translation of UML Activities into PROforma T2 - 2019 International Conference on Computational Science and Computational Intelligence (CSCI) N2 - In modern medicine, Clinical Practice Guidelines (CPGs) are well-established resources for the appropriate treatment of diseases. Evidence-based CPGs contain recommendations which are based on the state of the art and which have been achieved by consensus of several experts. Nevertheless, there is a potential for problems in translating guideline documents into specific actions for physicians. Therefore we propose to formalize the treatment process in an understandable representation as UML activities together with a domain expert. This formalization serves as a basis for the transfer of knowledge into a model, in this case PROforma, which directly allows execution in an interactive assistance software. The results of this work are part of an ongoing research project on the treatment of colon cancer based on the corresponding evidence-based CPG. KW - Clinical Practice Guidelines KW - Medical Treatment KW - Assistance Y1 - 2021 UR - https://doi.org/10.1109/CSCI49370.2019.00184 SP - 972 EP - 976 ER - TY - CHAP A1 - Philipp, Patrick A1 - Bommersheim, Marie A1 - Robert, Sebastian A1 - Beyerer, Jürgen T1 - Probabilistic Estimation of Human Interaction Needs in Context of a Robotic Assistance in Geriatrics T2 - Current Directions in Biomedical Engineering N2 - The key purpose of assistance robots is to help people coping with work-related or everyday tasks. To ensure an intuitive and effective support by an assistance robot, its expectation conform behavior is essential. In particular, when using assistance robots in geriatrics to assist elderly patients, special attention to the human-robot interaction should be paid. In order to help elderly patients maintain their independence and abilities as much as possible, the robot should only intervene when its support is needed. Therefore, the continuous estimation of the patient’s need for interaction is of particular importance. For enabling suitable models to estimate this need, we elaborate the use of Bayesian Networks. The analysis of our results seems promising, yielding a robust and practical approach. KW - Bayesian Networks KW - Virtual Evidence KW - Robotics KW - Gerontology KW - Social Robot KW - Assistance Technology Y1 - 2021 UR - https://doi.org/10.1515/cdbme-2019-0109 SP - 433 EP - 436 ER - TY - CHAP A1 - Mucha, Henrik A1 - Jacobi, Ricarda A1 - Robert, Sebastian T1 - Partizipation und Künstliche Intelligenz T2 - Mensch und Computer 2019 - Workshopband N2 - Der Einsatz künstlicher Intelligenz (KI) wird unsere Lebenswirklichkeit nachhaltig beeinflussen. Mittels technischer Verfahren maschinellen Lernens oder tiefer neuronaler Netze können Modelle aus existierenden Datenbeständen gelernt und Vorhersagen abgeleitet werden. Wir stellen skizzenartig zwei aktuelle Projekte vor, die sich u.a. mit den Potentialen und der menschzentrierten Gestaltung von Systemen künstlicher Intelligenz beschäftigen. Wir betten dies schlaglichtartig in den Kontext der aktuellen Debatte über die Entwicklung und Gestaltung von KI Systemen ein. Im Zuge dessen umreißen wir Herausforderungen und Chancen für die partizipative und sozialverantwortliche Technologieentwicklung von komplexen und auf Verfahren der künstlichen Intelligenz basierenden Systemen. Schließlich fokussieren wir dabei auf die Arbeitsebene und beschreiben kurz, welche konkreten Aktivitäten wir planen und stellen diese zur Diskussion. KW - Partizipation KW - Künstliche Intelligenz KW - Design Y1 - 2021 UR - https://doi.org/10.18420/muc2019-ws-413 SP - 19 EP - 21 ER - TY - JOUR A1 - Hempel, Louisa A1 - Veloso de Oliveira, Julia A1 - Gaumann, Andreas A1 - Milani, Valeria A1 - Schweneker, Katrin A1 - Schenck, Kristina A1 - Fleischmann, Bastian A1 - Philipp, Patrick A1 - Mederle, Stefanie A1 - Garg, Arun A1 - Piehler, Armin A1 - Gandorfer, Beate A1 - Schick, Cordula A1 - Kleespies, Axel A1 - Sellmann, Ludger A1 - Bartels, Marius A1 - Goetze, Thorsten O. A1 - Stein, Alexander A1 - Goekkurt, Eray A1 - Pfitzner, Lucia A1 - Robert, Sebastian A1 - Hempel, Dirk T1 - Landscape of Biomarkers and Actionable Gene Alterations in Adenocarcinoma of GEJ and Stomach - A Real World Data Analysis JF - Cancers N2 - After several years of negative phase III trials in gastric and esophageal cancer, a significant breakthrough in the treatment of metastatic adenocarcinomas of the gastroesophageal junction (GEJ) and stomach (GC) is now becoming evident with the emerging of precision oncology and implementation of molecular targets in tumor treatment. In addition, new generation studies such as umbrella and basket trials are focused on these molecular targets, which makes an early molecular diagnosis based on IHC/ISH and NGS necessary. The required companion diagnostics of Her2neu overamplification or PD-L1 expression is based on immunohistochemistry (IHC) or additionally in situ hybridization (ISH) in case of an IHC Her2neu score of 2+. However, there are investigator-dependent differences in the assessment of Her2neu amplification and different PD-L1 scoring systems obtained by IHC/ISH. The use of high-throughput technologies such as next-generation sequencing (NGS) holds the potential to standardize the analysis and thus make them more comparable. In the presented study, real-world multigene sequencing data of 72 Caucasian patients diagnosed with metastatic adenocarcinomas of GEJ and stomach were analyzed. In the clinical companion diagnostics, we found ESCAT level I molecular targets in one-third of our patients, which directly determined the therapy. In addition, we found potential targets in 14/72 patients (19.4%) who potentially qualify for precision therapies in corresponding molecular studies. The study highlights the importance of comprehensive molecular profiling for precision treatment of GEJ/GC and indicates that a biomarker evaluation should be performed for all patients with metastatic adenocarcinomas before the initiation of first-line treatment and during second-line or subsequent treatment. KW - GEJ KW - GC KW - next-generation sequencing KW - Her2neu KW - PD-L1 KW - personalized medicine KW - molecular target KW - checkpoint inhibitors KW - actionable gene variants Y1 - 2021 UR - https://doi.org/10.3390/cancers13174453 VL - 13 IS - 17 SP - 4453 ER - TY - JOUR A1 - Hempel, Louisa A1 - Molnar, Jakob A1 - Gaumann, Andreas A1 - Robert, Sebastian A1 - Scheiber, Josef A1 - Kleespies, Axel A1 - Riedmann, Kristina A1 - Schreiber, Susanne A1 - Gandorfer, Beate A1 - Piehler, Armin A1 - Hempel, Dirk T1 - Detection of acquired resistance mutation ALK G1202R after treatment with alectinib and response of lorlatinib BT - A case report JF - memo - Magazine of European Medical Oncology N2 - In the era of personalized medicine, the identification of driver mutations has paved the way towards targeted therapy. With the identification of anaplastic lymphoma kinase (ALK) as an oncogenic driver mutation, ALK rearrangements became druggable by tyrosine kinase inhibitors and, thus, have improved the prognosis for patients. Nevertheless, these approaches are limited by resistances occurring within the first or second year of administering ALK inhibitors. Among the different ALK resistant mutations, G1202R is the most common mutation, located in the kinase domain of the ALK protein resulting in resistance to treatment with the first- and second-generation kinase inhibitors (e.g., crizotinib, ceritinib, brigatenib and alectinib). Conflicting reports exist regarding the efficacy of lorlatinib, a next generation ALK inhibitor. The aim of this study is to access the potential impact of lorlatinib as a second-line treatment for a metastatic progressive NSCLC disease harboring genomic alteration of ALK G1202R, an AKLi-resistant mutation. The case of a patient with advanced lung cancer and the mentioned mutation is described. KW - NSCLC KW - Next-generation ALK inhibitor KW - Resistance mechanisms KW - Next-generation sequencing KW - Molecular diagnostics Y1 - 2021 UR - https://doi.org/10.1007/s12254-021-00724-2 ER - TY - CHAP A1 - Mucha, Henrik A1 - Robert, Sebastian A1 - Breitschwerdt, Ruediger A1 - Fellmann, Michael T1 - Interfaces for Explanations in Human-AI Interaction: Proposing a Design Evaluation Approach T2 - Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA N2 - Explanations in Human-AI Interaction are communicated to human decision makers through interfaces. Yet, it is not clear what consequences the exact representation of such explanations as part of decision support systems (DSS) and working on machine learning (ML) models has on human decision making. We observe a need for research methods that allow for measuring the effect different eXplainable AI (XAI) interface designs have on people’s decision making. In this paper, we argue for adopting research approaches from decision theory for HCI research on XAI interface design. We outline how we used estimation tasks in human-grounded design research in order to introduce a method and measurement for collecting evidence on XAI interface effects. To this end, we investigated representations of LIME explanations in an estimation task online study as proof-of-concept for our proposal. KW - Human-AI Interaction Y1 - 2021 UR - https://doi.org/10.1145/3411763.3451759 SP - 327 ER - TY - CHAP A1 - Mucha, Henrik A1 - Mevißen, Dennis A1 - Robert, Sebastian A1 - Jacobi, Ricarda A1 - Meyer, Kirsten A1 - Heusler, Winfried A1 - Arztmann, Daniel T1 - Co-Design Futures for AI and Space: A Workbook Sprint T2 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (CHI EA '20). Association for Computing Machinery, New York, NY, USA N2 - Artificial Intelligence (AI) is continuously moving into our surroundings. In its various forms, it has the potential to disrupt most aspects of human life. Yet, the discourse around AI has long been by experts and for experts. In this paper, we argue for a participatory approach towards designing human-AI interactions. We outline how we used design methodology to organise an interdisciplinary workshop with a diverse group of students – a workbook sprint with 45 participants from four different programs and 13 countries – to develop speculative design futures in five focus areas. We then provide insights into our findings and share our lessons learned regarding our workshop topic – AI and Space – our process, and our research. We learned that involving non-experts in complex technical discourses – such as AI – through the structural rigour of design methodology is a viable approach. We then conclude by laying out how others might use our findings and initiate their own workbook sprint to explore complex technologies in a human-centred way. KW - Artificial Intelligence Y1 - 2021 UR - https://doi.org/10.1145/3334480.3375203 SP - 1 EP - 8 ER - TY - JOUR A1 - Hempel, Louisa A1 - Molnar, Jakob A1 - Robert, Sebastian A1 - Veloso, Julia A1 - Trepotec, Zeljka A1 - Englisch, Sofie A1 - Weinzierl, Philip A1 - Schick, Cordula A1 - Milani, Valeria A1 - Schweneker, Katrin A1 - Fleischmann, Bastian A1 - Scheiber, Josef A1 - Gandorfer, Beate A1 - Kleespies, Axel A1 - Hempel, Dirk A1 - Riedmann, Kristina A1 - Piehler, Armin T1 - Rare SARS-CoV-2 antibody development in cancer patients JF - Seminars in Oncology N2 - SARS-CoV-2 antibody development and immunity will be crucial for the further course of the pandemic. Until now, it has been assumed that patients who are infected with SARS-CoV-2 will develop antibodies as has been the case with other coronaviruses, like MERS-CoV and SARS-CoV. In the present study, we analyzed the development of antibodies in 77 patients with an oncologic diagnosis 26 days after positive RT-qPCR testing for SARS-CoV2. RT-qPCR and anti-SARS-CoV2-antibody methods from BGI (MGIEasy Magnetic Beads Virus DNA/RNA Extraction Kit) and Roche (Elecsys Anti-SARS-CoV-2 immunoassay) were used, respectively, according to the manufacturers’ specifications. Surprisingly, antibody development was detected in only 6 of 77 individuals with a confirmed history of COVID-19. Despite multiple testing, the remaining patients did not show measurable antibody concentrations in subsequent tests. These results undermine the previous hypothesis that SARS-CoV2 infections are regularly associated with antibody development and cast doubt on the provided immunity to COVID-19. Understanding the adaptive and humoral response to SARS-CoV2 will play a key role in vaccine development and gaining further knowledge on the pathogenesis. KW - SARS-CoV2 antibody development KW - COVID-19 KW - Cancer KW - Immunity Y1 - 2021 UR - https://doi.org/10.1053/j.seminoncol.2020.12.003 VL - 48 IS - 2 SP - 160 EP - 165 ER - TY - CHAP A1 - Mucha, Henrik A1 - Robert, Sebastian A1 - Breitschwerdt, Rüdiger A1 - Fellmann, Michael T1 - Towards Participatory Design Spaces for Explainable AI Interfaces in Expert Domains T2 - CEUR Workshop Proceedings XI-ML 2020 N2 - In this position paper, we lay out an approach to use participatory and co-design methodology to explore how users perceive and interact with explanations of artificially intelligent decision support systems. We describe how we intend to construct bottom-up participatory design spaces to systematically inform the design of interactive explanations in Human-AI interaction. KW - Explainable AI (XAI) KW - Participatory Design KW - Design Spaces Y1 - 2021 ER -