ProCLAIM: an argument-based model for deliberating over safety critical actions

In this Thesis we present an argument-based model – ProCLAIM – intended to provide a setting for heterogeneous agents to deliberate on whether a proposed action is safe. That is, whether or not a proposed action is expected to cause some undesirable side effect that will justify not to undertake the proposed action. This is particularly relevant in safetycritical environments where the consequences ensuing from an inappropriate action may be catastrophic. For the practical realisation of the deliberations the model features a mediator agent with three main tasks: 1) guide the participating agents in what their valid argumentation moves are at each stage of the deliberation; 2) decide whether submitted arguments should be accepted on the basis of their relevance; and finally, 3) evaluate the accepted arguments in order to provide an assessment on whether the proposed action should or should not be undertaken, where the argument evaluation is based on domain consented knowledge (e.g guidelines and regulations), evidence and the decision makers’ expertise. To motivate ProCLAIM’s practical value and generality the model is applied in two scenarios: human organ transplantation and industrial wastewater. In the former scenario, ProCLAIM is used to facilitate the deliberation between two medical doctors on whether an available organ for transplantation is or is not suitable for a particular potential recipient (i.e. whether it is safe to transplant the organ). In the later scenario, a number of agents deliberate on whether an industrial discharge is environmentally safe.En esta tesis se presenta un modelo basado en la Argumentación –ProCLAIM– cuyo n es proporcionar un entorno para la deliberación sobre acciones críticas para la seguridad entre agentes heterogéneos. En particular, el propósito de la deliberación es decidir si los efectos secundario indeseables de una acción justi can no llevarla a cabo. Esto es particularmente relevante en entornos críticos para la seguridad, donde las consecuencias que se derivan de una acción inadecuada puede ser catastró cas. Para la realización práctica de las deliberaciones propuestas, el modelo cuenta con un agente mediador con tres tareas principales: 1) guiar a los agentes participantes indicando cuales son las líneas argumentación válidas en cada etapa de la deliberación; 2) decidir si los argumentos presentados deben ser aceptadas sobre la base de su relevancia y, por último, 3) evaluar los argumentos aceptados con el n de proporcionar una valoración sobre la seguridad de la acción propuesta. Esta valoración se basa en guías y regulaciones del dominio de aplicación, en evidencia y en la opinión de los expertos responsables de la decisión. Para motivar el valor práctico y la generalidad de ProCLAIM, este modelo se aplica en dos escenarios distintos: el trasplante de órganos y la gestión de aguas residuales. En el primer escenario el modelo se utiliza para facilitar la deliberación entre dos médicos sobre la viabilidad del transplante de un órgano para un receptor potencial (es decir, si el transplante es seguro). En el segundo escenario varios agentes deliberan sobre si los efectos de un vertido industrial con el propósito de minimizar su impacto medioambiental

Goal-Driven Structured Argumentation for Patient Management in a Multimorbidity Setting

We use computational argumentation to both analyse and generate solutions for reasoning in multimorbidity about consistent recommendations, according to different patient-centric goals. Reasoning in this setting carries a complexity related to the multiple variables involved. These variables reflect the co-existing health conditions that should be considered when defining a proper therapy. However, current Clinical Decision Support Systems (CDSSs) are not equipped to deal with such a situation. They do not go beyond the straightforward application of the rules that build their knowledge base and simple interpretation of Computer-Interpretable Guidelines (CIGs). We provide a computational argumentation system equipped with goal-seeking mechanisms to combine independently generated recommendations, with the ability to resolve conflicts and generate explanations for its results. We also discuss its advantages over and relation to Multiple-criteria Decision-making (MCDM) in this particular setting.- (undefined

Dialogue games for explaining medication choices

SMT solvers can be used efficiently to search for optimal paths across multiple graphs when optimising for certain resources. In the medical context, these graphs can represent treatment plans for chronic conditions where the optimal paths across all plans under consideration are the ones which minimize adverse drug interactions. The SMT solvers, however, work as a black-box model and there is a need to justify the optimal plans in a human-friendly way. We aim to fulfill this need by proposing explanatory dialogue protocols based on computational argumentation to increase the understanding and trust of humans interacting with the system. The protocols provide supporting reasons for nodes in a path and also allow counter reasons for the nodes not in the graph, highlighting any potential adverse interactions during the dialogue.Postprin

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Design rationale for the regulatory approval of medical devices

Design rationale is a methodology aimed at capturing and representing design decisions according to a designated structure. Additionally, these design decisions and their underlying arguments can be made available for examination at a later date. The literature review identified that there is currently a lack of information describing the use of design rationale methods and computational support tools with the medical device domain. Furthermore, the review of literature has also recognised that there are no existing guidelines available for medical device manufacturers and regulatory authorities to follow in order to capture and represent the design decisions in the case of medical devices. Medical devices are instruments which are used for diagnosis, screening, monitoring, or the treating of patients suffering from disease, injury, or disability. Medical devices are products that require rigorous regulation before they can be placed onto the market. If problems are encountered with a device once it has been placed onto the market, the device is recalled by the relevant regulatory authority. Device recalls can often result in the device manufacturers having to evaluate the design decisions that were made during the product development stages in order to address the reported problems and implement a solution. As a result, medical device manufacturers can incur unexpected rework and/or redesign costs, and in even more severe circumstances, incur high litigation costs. This research; reviews the state-of-the-art in design rationale and identifies its key capabilities, analyses design rationale’s feasibility for use with the medical device domain, identifies the regulatory approval processes for medical devices and compares them, analyses the possibilities of utilising design rationale with the regulatory approval of medical devices, and develops a set of guidelines. The guidelines detail the necessary steps that are required to capture and represent the design decisions for medical devices. The utility of this contribution has been verified through the process of validation with experts and researchers.Engineering and Physical Sciences Research Counci

Argumentation Mining in User-Generated Web Discourse

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task.Comment: Cite as: Habernal, I. & Gurevych, I. (2017). Argumentation Mining in User-Generated Web Discourse. Computational Linguistics 43(1), pp. 125-17

A framework for decision making on teleexpertise with traceability of the reasoning

This paper provides a methodological framework for decision making process to ensure its traceability generally in the context of telemedicine and particularly in the act of teleexpertise. This act permits to medical professionals and/or health professionals to collaborate in order to take suitable decisions for a patient diagnosis or treatment. The main problem dealing with teleexpertise is the following: How to ensure the traceability of the decisions making process? This problem is solved in this paper through a conceptualisation of a rigorous framework coupling semantic modelling and explicit reasoning which permits to fully support the analysis and rationale for decisions made. The logical semantic underlying this framework is the argumentative logicto provide adequate management of information with traceability of the reasoning including options and constraints. Thus our proposal will permit to formally ensure the traceability of reasoning in telemedicine and particularly in teleexpertise in order to favour the quality of telemedicine’s procedure checking. This traceability is to guarantee equitable access to the benefits of the collective knowledge and experience and to provide remote collaborative practices with a sufficient safety margin to guard against the legal requirements. An illustrative case study is provided by the modelling of a decision making process applied to teleexpertise for chronic diseases such as diabetes mellitus type2