42 research outputs found

    Measuring the impact of COVID-19 on hospital care pathways

    Get PDF
    Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted

    Improving Formal Explanations in AI

    Get PDF
    Within the field of explainable AI, a considerable drawback of the current explanation methods is that they do not take background knowledge into account to improve the quality of explanations. We study this problem and present a mechanism to include arbitrary background knowledge on the input domain as constraints into the reasoning process. We show, theoretically and empirically, that the quality of explanations can be enhanced by 1) using domain constraints to improve the parsimony of explanations, and 2) producing more focused explanations by specifying a "context" for an explanation (i.e. a cover and a partial world). Further, we investigate the close connection between explanations and causality by formalising a few relevant concepts and notions from the social science literature. We illustrate the usefulness of these formalised notions for making causal arguments over some canonical examples from the causality literature. Finally, we provide the details of a quantitative approach to improving explanation quality by using a real-life example from medical domains

    Building bridges for better machines : from machine ethics to machine explainability and back

    Get PDF
    Be it nursing robots in Japan, self-driving buses in Germany or automated hiring systems in the USA, complex artificial computing systems have become an indispensable part of our everyday lives. Two major challenges arise from this development: machine ethics and machine explainability. Machine ethics deals with behavioral constraints on systems to ensure restricted, morally acceptable behavior; machine explainability affords the means to satisfactorily explain the actions and decisions of systems so that human users can understand these systems and, thus, be assured of their socially beneficial effects. Machine ethics and explainability prove to be particularly efficient only in symbiosis. In this context, this thesis will demonstrate how machine ethics requires machine explainability and how machine explainability includes machine ethics. We develop these two facets using examples from the scenarios above. Based on these examples, we argue for a specific view of machine ethics and suggest how it can be formalized in a theoretical framework. In terms of machine explainability, we will outline how our proposed framework, by using an argumentation-based approach for decision making, can provide a foundation for machine explanations. Beyond the framework, we will also clarify the notion of machine explainability as a research area, charting its diverse and often confusing literature. To this end, we will outline what, exactly, machine explainability research aims to accomplish. Finally, we will use all these considerations as a starting point for developing evaluation criteria for good explanations, such as comprehensibility, assessability, and fidelity. Evaluating our framework using these criteria shows that it is a promising approach and augurs to outperform many other explainability approaches that have been developed so far.DFG: CRC 248: Center for Perspicuous Computing; VolkswagenStiftung: Explainable Intelligent System

    Research Paper: Process Mining and Synthetic Health Data: Reflections and Lessons Learnt

    Get PDF
    Analysing the treatment pathways in real-world health data can provide valuable insight for clinicians and decision-makers. However, the procedures for acquiring real-world data for research can be restrictive, time-consuming and risks disclosing identifiable information. Synthetic data might enable representative analysis without direct access to sensitive data. In the first part of our paper, we propose an approach for grading synthetic data for process analysis based on its fidelity to relationships found in real-world data. In the second part, we apply our grading approach by assessing cancer patient pathways in a synthetic healthcare dataset (The Simulacrum provided by the English National Cancer Registration and Analysis Service) using process mining. Visualisations of the patient pathways within the synthetic data appear plausible, showing relationships between events confirmed in the underlying non-synthetic data. Data quality issues are also present within the synthetic data which reflect real-world problems and artefacts from the synthetic dataset’s creation. Process mining of synthetic data in healthcare is an emerging field with novel challenges. We conclude that researchers should be aware of the risks when extrapolating results produced from research on synthetic data to real-world scenarios and assess findings with analysts who are able to view the underlying data

    Advancing natural language processing in political science

    Get PDF

    Implizites Wissen

    Get PDF
    Expertise und Könnerschaft greifen auf implizites Wissen zurück, das jenseits von Routinen angesiedelt ist. Die Autorinnen und Autoren untersuchen Formen impliziten Wissens in beruflichen und betrieblichen Handlungsfeldern und inwieweit sich diese gezielt anleiten und vermitteln lassen. Der Sammelband enthält konzeptionelle Beiträge und empirische Arbeiten aus verschiedenen beruflichen Domänen sowie aus der Wirtschafts- und Unternehmensethik. Die Texte sind folgenden Schwerpunkten zugeordnet: implizites Wissen in beruflichen Domänen, Lernen und Erwerb impliziten Wissens, Regeln als soziale Praxen sowie implizites Wissen im Kontext von Moral und Digitalisierung

    Symbolic XAI: automatic programming II

    Full text link
    Explainable artificial intelligence (XAI) is a field blooming right now. With the popularity of opaque systems, the need of explanation methods that shed light on how this systems works has risen as well. In this work, we propose the usage of symbolic machine learning systems as explanation methods, a line that is yet to be fully explored. We will do this by reviewing this symbolic systems, analyzing the existing taxonomies of explanation methods and fitting the systems within the taxonomies. Finally, we will also do some testing on solving numerical problems with symbolic systems

    Practical Algorithms for Resource Allocation and Decision Making

    Get PDF
    Algorithms are widely used today to help make important decisions in a variety of domains, including health care, criminal justice, employment, and education. Designing \emph{practical} algorithms involves balancing a wide variety of criteria. Deployed algorithms should be robust to uncertainty, they should abide by relevant laws and ethical norms, they should be easy to use correctly, they should not adversely impact user behavior, and so on. Finding an appropriate balance of these criteria involves technical analysis, understanding of the broader context, and empirical studies ``in the wild''. Most importantly practical algorithm design involves close collaboration between stakeholders and algorithm developers. The first part of this thesis addresses technical issues of uncertainty and fairness in \emph{kidney exchange}---a real-world matching market facilitated by optimization algorithms. We develop novel algorithms for kidney exchange that are robust to uncertainty in both the quality and the feasibility of potential transplants, and we demonstrate the effect of these algorithms using computational simulations with real kidney exchange data. We also study \emph{fairness} for hard-to-match patients in kidney exchange. We close a previously-open theoretical gap, by bounding the price of fairness in kidney exchange with chains. We also provide matching algorithms that bound the price of fairness in a principled way, while guaranteeing Pareto efficiency. The second part describes two real deployed algorithms---one for kidney exchange, and one for recruiting blood donors. For each application cases we characterize an underlying mathematical problem, and theoretically analyze its difficulty. We then develop practical algorithms for each setting, and we test them in computational simulations. For the blood donor recruitment application we present initial empirical results from a fielded study, in which a simple notification algorithm increases the expected donation rate by 5%5\%. The third part of this thesis turns to human aspects of algorithm design. We conduct several survey studies that address several questions of practical algorithm design: How do algorithms impact decision making? What additional information helps people use complex algorithms to make decisions? Do people understand standard algorithmic notions of fairness? We conclude with suggestions for facilitating deeper stakeholder involvement for practical algorithm design, and we outline several areas for future research

    Jahresbericht der Research Academy Leipzig 2013

    Get PDF
    Jahresbericht der Research Academy Leipzig 201

    Jahresbericht der Research Academy Leipzig 2007

    Get PDF
    Jahresbericht der Research Academy Leipzig 2007:Inhalt - Die Research Academy Leipzig - Rede zum einjährigen Jubiläum der Gründung der Research Academy Leipzig - Die Vorteile von Promotionsschulen Eine Betreuerperspektive - Fächerübergreifende Qualifikationsmaßnahmen: Die Veranstaltungen der Research Academy Leipzig 2007 - Präsentation in der Öffentlichkeit - Kleinkindbetreuung für Kinder der Doktorandinnen und Doktoranden - Das Graduiertenzentrum Mathematik/Informatik und Naturwissenschaften - Graduiertenschule Leipzig School of Natural Sciences – Building with Molecules and Nano-objects BuildMoNa - Deutsch-Französisches Doktorandenkollegium Statistical Physics of Complex Systems - International Max Planck Research School Mathematics in the Sciences - International Research Training Group Diffusion in Porous Materials - Graduiertenkolleg Analysis, Geometrie und ihre Verbindung zu den Naturwissenschaften - Graduiertenkolleg Wissensrepräsentation - Graduiertenkolleg Mechanistische und Anwendungsaspekte nichtkonventioneller Oxidationsreaktionen - Internationales Promotionsprogramm Forschung in Grenzgebieten der Chemie - Das Graduiertenzentrum Lebenswissenschaften - Graduiertenkolleg Interdisziplinäre Ansätze in den Neurowissenschaften InterNeuro - Graduiertenkolleg Funktion von Aufmerksamkeit bei kognitiven Prozessen - Internationales Promotionsprogramm Von der Signalverarbeitung zum Verhalten IPP Signal - International Max Planck Research School The Leipzig School of Human Origins - MD-PhD-Programm der Universität Leipzig - Graduiertenkolleg Universalität und Diversität: Sprachliche Strukturen und Prozesse - Das Graduiertenzentrum Geistes- und Sozialwissenschaften - Internationales Promotionsprogramm Transnationalisierung und Regionalisierung vom 18. Jahrhundert bis zur Gegenwart - Graduiertenkolleg Bruchzonen der Globalisierung - Deutsch als Fremdsprache Transcultural German Studies - Kultureller Austausch Altertumswissenschaftliche, historische und ethnologische Perspektiven - Praktiken gesellschaftlicher Raumproduktionen in Europa Geographische, historische und soziologische Perspektiven - Bildnachweise - Impressu
    corecore