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Auflistung Künstliche Intelligenz 29(2) - Mai 2015 nach Titel
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- ZeitschriftenartikelA Paradigm Shift in Healthcare Provision(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Sonntag, Daniel; Gelissen, Jean
- ZeitschriftenartikelAn Interactive Narrative Format for Clinical Guidelines(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Cavazza, Marc; Charles, Fred; Lindsay, Alan; Siddle, Jonathan; Georg, GersendeClinical guidelines are standardised documents, which summarise best practice in complex medical situations. Their target audience comprises health professionals, or in some cases patient groups, for whom they constitute important sources of patient education. These documents are characterised by a rich knowledge content, which also relies on a complex, largely implicit background. At the heart of guidelines is a set of recommendations describing expected behaviour throughout specific, evolving contexts. Such complex documents can be challenging to assimilate, in particular their patient education versions. The need to contextualise information and visualise behaviours and their consequences suggests the use of virtual environments, as in serious gaming. However, knowledge representation in serious games are often limited and the overall implementation mainly empirical. On the other hand, interactive narratives technologies have demonstrated their ability to embed complex behavioural knowledge and support principled behaviour responding to dynamic contexts. This is why they support the exploration of complex situations, their rehearsal, and the understanding of expected behaviour through what-if interaction. The narrative perspective also provides better user guidance than a pure simulation system, allowing mixed-initiative access to information. The translation of medical protocols as interactive narratives is faced with a number of knowledge representation challenges, in particular for the representation of non-compli-ance and the consequences of incorrect behaviour. Another technical issue is the need to represent both common sense and domain knowledge, and articulate their representation with the Planning domain that forms the backbone of the interactive narrative. As part of the Open FET project MUSE (FP7-296703), we are developing a proof-of-concept prototype exploring the above aspects, and embedding the logical structure of guidelines into a real-time interactive narrative, which provides a principled simulation of the situations faced by patients, which preserves causal and deontic constraints. This paper describes the knowledge engineering process supporting the development of this prototype, from the analysis of patient guidelines to the use of planning representations supporting the interactive narrative.
- ZeitschriftenartikelCognitive Endurance for Brain Health: Challenges of Creating an Intelligent Warning System(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Hedman, Anders; Hallberg, JosefDuring the past few years, the market for apps monitoring traditional health and wellbeing parameters such as heart rate, levels of physical activity and sleep patterns has rapidly expanded. In this paper, we articulate how we are currently engineering an early warning system designed to support long-term brain health, termed cognitive endurance, based on such monitoring. It can be thought of as a rudimentary expert system. It will monitor physical and social activity, stress and sleep patterns and signal when these parameters are such that a person’s cognitive endurance might be at risk. The aim of the system is to guide the user to adopt sustainable behavioral patterns from a cognitive endurance perspective. This paper articulates (1) what we mean by cognitive endurance, (2) how cognitive endurance may be enhanced, (3) our cognitive endurance monitoring platform, (4) our approach to calculating cognitive endurance risk, (5) specific challenges related to our approach and (6) what the long term benefits might be of successively monitoring cognitive endurance.
- ZeitschriftenartikelExploiting Latent Embeddings of Nominal Clinical Data for Predicting Hospital Readmission(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Krompaß, Denis; Esteban, Cristóbal; Tresp, Volker; Sedlmayr, Martin; Ganslandt, ThomasHospital readmissions of patients put a high burden not only on the health care system, but also on the patients since complications after discharge generally lead to additional burdens. Estimating the risk of readmission after discharge from inpatient care has been the subject of several publications in recent years. In those publications the authors mostly tried to directly infer the readmission risk (within a certain time frame) from the clinical data recorded in the medical routine such as primary diagnosis, co-morbidities, length of stay, or questionnaires. Instead of using these data directly as inputs for a prediction model, we are exploiting latent embeddings for the nominal parts of the data (e.g., diagnosis and procedure codes). These latent embeddings have been used with great success in the natural language processing domain and can be constructed in a preprocessing step. We show in our experiments, that a prediction model that exploits these latent embeddings can lead to improved readmission predictive models.
- ZeitschriftenartikelFacilitating Evolution during Design and Implementation(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) McClatchey, RichardThe volumes and complexity of data that companies need to handle are increasing at an accelerating rate. In order to compete effectively and ensure their commercial sustainability, it is becoming crucial for them to achieve robust traceability in both their data and the evolving designs of their systems. This is addressed by the CRISTAL software which was originally developed at CERN by UWE, Bristol, for one of the particle detectors at the Large Hadron Collider, which has been subsequently transferred into the commercial world. Companies have been able to demonstrate increased agility, generate additional revenue, and improve the efficiency and cost-effectiveness with which they develop and implement systems in various areas, including business process management (BPM), healthcare and accounting applications. CRISTAL’s ability to manage data and its semantic provenance at the terabyte scale, with full traceability over extended timescales, together with its description-driven approach, has provided the flexible adaptability required to future proof dynamically evolving software for these businesses.
- ZeitschriftenartikelIs it Research or is it Spying? Thinking-Through Ethics in Big Data AI and Other Knowledge Sciences(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Berendt, Bettina; Büchler, Marco; Rockwell, Geoffrey“How to be a knowledge scientist after the Snowden revelations?” is a question we all have to ask as it becomes clear that our work and our students could be involved in the building of an unprecedented surveillance society. In this essay, we argue that this affects all the knowledge sciences such as AI, computational linguistics and the digital humanities. Asking the question calls for dialogue within and across the disciplines. In this article, we will position ourselves with respect to typical stances towards the relationship between (computer) technology and its uses in a surveillance society, and we will look at what we can learn from other fields. We will propose ways of addressing the question in teaching and in research, and conclude with a call to action.
- ZeitschriftenartikelKI Fachbereichspolitik und Künstliche Kognitive Systeme(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Visser, Ubbo
- ZeitschriftenartikelNews(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015)
- ZeitschriftenartikelNow All Together: Overview of Virtual Health Assistants Emulating Face-to-Face Health Interview Experience(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Lisetti, Christine; Amini, Reza; Yasavur, UganWe discuss a large research project aimed at building socially expressive virtual health agents or assistants (VHA) that can deliver brief motivational interventions (BMI) for behavior change, in a communication style that individuals and patients not only accept, but also find emotionally supportive and socially appropriate. Because of their well-defined sequential structure, BMIs lend themselves well to automation, and are adaptable to address a variety of target behaviors, from obesity, to alcohol and drug use, to lack treatment adherence, among others. We discuss the advantages that VHAs provide for the delivery of health interventions. We describe components of our intelligent agent architecture that enables our virtual health agents to dialogue with users in realtime while delivering the appropriate intervention based on the patient’s specific needs at the time. We conclude by identifying open research challenges in developing virtual health agents.
- ZeitschriftenartikelPersonalized Stress Management: Enabling Stress Monitoring with LifelogExplorer(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Kocielnik, Rafal; Sidorova, NataliaStress is one of the major triggers for many diseases. Improving stress balance is therefore an important prevention step. With advances in wearable sensors, it becomes possible to continuously monitor and analyse user’s behavior and arousal in an unobtrusive way. In this paper, we report on a case study in which users (21 teachers of a vocational school) were provided with wearable sensors and could view their arousal information put in the context of their life events during the period of four weeks using our software tool in an unsupervised setting. The goal was to evaluate user engagement and enabling of self-coaching abilities. Our results show that users actively explored their arousal data during the study. Further qualitative evaluation conducted with 15 of 21 users indicated that 12 of 15 users were able to learn about their stress patterns based on the information they obtained, but only 5 of them were able to come up with practical interventions for improving their stress balance on their own, while other users were of opinion that nothing can be done to reduce their stress, which suggests that self-coaching has some potential but there is need in further coaching support.