Decision Support and Knowledge Management in Oncology using Hierarchical Classification

Colloque avec actes et comité de lecture. internationale.International audienceThis paper presents the Kasimir research project for the management of decision protocols in oncology. A decision protocol is a kind of decision tree implemented in an object-based representation formalism. A reasoner based on such a formalism and on hierarchical classification is coupled with a knowledge editor. This association provides an assistance for editing and maintenance of protocols, enabling the detection of errors and the comparison between versions of the protocol. In this way, a management of protocols takes fully advantage of the underlying knowledge representation and reasoning tools. This straightforward use of the protocol may be insufficient in some situations. Then, the protocol may have to be adapted for these situations. A study of protocol adaptation is presented. In particular a reasoner based on a combination of hierarchical classification and fuzzy logic is introduced

Horizon Report 2009

El informe anual Horizon investiga, identifica y clasifica las tecnologías emergentes que los expertos que lo elaboran prevén tendrán un impacto en la enseñanza aprendizaje, la investigación y la producción creativa en el contexto educativo de la enseñanza superior. También estudia las tendencias clave que permiten prever el uso que se hará de las mismas y los retos que ellos suponen para las aulas. Cada edición identifica seis tecnologías o prácticas. Dos cuyo uso se prevé emergerá en un futuro inmediato (un año o menos) dos que emergerán a medio plazo (en dos o tres años) y dos previstas a más largo plazo (5 años)

Doctor of Philosophy

dissertationThe use of the various complementary and alternative medicine (CAM) modalities for the management of chronic illnesses is widespread, and still on the rise. Unfortunately, tools to support consumers in seeking information on the efficacy of these treatments are sparse and incomplete. The goals of this work were to understand CAM information needs in acquiring CAM information, assess currently available information resources, and investigate informatics methods to provide a foundation for the development of CAM information resources. This dissertation consists of four studies. The first was a quantitative study that aimed to assess the feasibility of delivering CAM-drug interaction information through a web-based application. This study resulted in an 85% participation rate and 33% of those patients reported the use of CAMs that had potential interactions with their conventional treatments. The next study aimed to assess online CAM information resources that provide information on drug-herb interactions to consumers. None of the sites scored high on the combination of completeness and accuracy and all sites were beyond the recommended reading level per the US Department of Health and Human Services. The third study investigated information-seeking behaviors for CAM information using an existing cohort of cancer survivors. The study showed that patients in the cohort continued to use CAM well into survivorship. Patients felt very much on their own in dealing with issues outside of direct treatment, which often resulted in a search for options and CAM use. Finally, a study was conducted to investigate two methods to semi-automatically extract CAM treatment relations from the biomedical literature. The methods rely on a database (SemMedDB) of semantic relations extracted from PubMed abstracts. This study demonstrated that SemMedDB can be used to reduce manual efforts, but review of the extracted sentences is still necessary due to a low mean precision of 23.7% and 26.4%. In summary, this dissertation provided greater insight into consumer information needs for CAM. Our findings provide an opportunity to leverage existing resources to improve the information-seeking experience for consumers through high-quality online tools, potentially moving them beyond the reliance on anecdotal evidence in the decision-making process for CAM

A Semantic Wiki for Editing and Sharing Decision Guidelines in Oncology

International audienceThe Internet has totally changed the way information is published and shared in medicine. With web 2.0 and semantic web technologies, web applications allow now collaborative information editing in a way that can be reused by machines. These new tools could be used to in local health networks to promote the editing and sharing of medical knowledge between practitioners. Oncolor, a French oncology network, has edited 144 decision guidelines. These local guidelines rely upon national French guidelines and are built and updated collaboratively by medical experts. To improve working conditions, the need of an online collaborative tool has been expressed. This paper presents OncoLogiK, a semantic wiki approach for local oncology guideline editing. Semantic wikis allow online collaborative work and manage semantic annotations which can be reused automatically to bring new services. Applied to oncology guidelines, semantic technologies improves the guideline management and provides additional services such as targeted queries to external bibliographical resources

Decentralized case-based reasoning and Semantic Web technologies applied to decision support in oncology

International audienceThis article presents the Kasimir system dedicated to decision knowledge management in oncology and which is built on top of Semantic Web technologies, taking benefit from standard knowledge representation formalisms and open reasoning tools. The representation of medical decision protocols, in particular for breast cancer treatment, is based on concepts and instances implemented within the description logic OWL DL. The knowledge units related to a protocol can then be applied for solving specific medical problems, using instance or concept classification. However, the straight application of a protocol is not always satisfactory, e.g., because of contraindications, necessitating an adaptation of the protocol. This is why the principles and methods of case-based reasoning in the framework of description logics have been used. In addition, the domain of oncology is complex and involves several specialties, e.g. surgery and chemotherapy. This complexity can be better undertaken with a viewpoint-based representation of protocols and viewpoint-based reasoning, for either application or adaptation of the protocols. Accordingly, a distributed description logic has been used for representing a viewpoint-based protocol. The application and the adaptation of the viewpoint-based protocol to medical cases is carried out using global instance classification and decentralized case-based reasoning

Where can teens find health information? A survey of web portals designed for teen health information seekers

The Web is an important source for health information for most teens with access to the Web (Gray et al, 2005a; Kaiser, 2001). While teens are likely to turn to the Web for health information, research has indicated that their skills in locating, evaluating and using health information are weak (Hansen et al, 2003; Skinner et al, 2003, Gray et al, 2005b). This behaviour suggests that the targeted approach to finding health information that is offered by web portals would be useful to teens. A web portal is the entry point for information on the Web. It is the front end, and often the filter, that users must pass through in order to link to actual content. Unlike general search engines such as Google, content that is linked to a portal has usually been pre-selected and even created by the organization that hosts the portal, assuring some level of quality control. The underlying architecture of the portal is structured and thus offers an organized approach to exploring a specific health topic. This paper reports on an environmental scan of the Web, the purpose of which was to identify and describe portals to general health information, in English and French, designed specifically for teens. It answers two key questions. First of all, what portals exist? And secondly, what are their characteristics? The portals were analyzed through the lens of four attributes: Usability, interactivity, reliability and findability. Usability is a term that incorporates concepts of navigation, layout and design, clarity of concept and purpose, underlying architecture, in-site assistance and, for web content with text, readability. Interactivity relates to the type of interactions and level of engagement required by the user to access health information on a portal. Interaction can come in the form of a game, a quiz, a creative experience, or a communication tool such as an instant messaging board, a forum or blog. Reliability reflects the traditional values of accuracy, currency, credibility and bias, and in the web-based world, durabililty. Findability is simply the ease with which a portal can be discovered by a searcher using the search engine that is most commonly associated with the Web by young people - Google - and using terms related to teen health. Findability is an important consideration since the majority of teens begin their search for health information using search engines (CIBER, 2008; Hansen et al, 2003). The content linked to by the portals was not evaluated, nor was the portals’ efficacy as a health intervention. Teens looking for health information on the Web in English have a wide range of choices available but French-language portals are much rarer and harder to find. A majority of the portals found and reviewed originated from hospitals, associations specializing in a particular disease, and governmental agencies, suggesting that portals for teens on health related topics are generally reliable. However, only a handful of the portals reviewed were easy to find, suggesting that valuable resources for teens remain buried in the Web

Policy needs and options for a common approach towards modelling and simulation of human physiology and diseases with a focus on the virtual physiological human.

Life is the result of an intricate systemic interaction between many processes occurring at radically different spatial and temporal scales. Every day, worldwide biomedical research and clinical practice produce a huge amount of information on such processes. However, this information being highly fragmented, its integration is largely left to the human actors who find this task increasingly and ever more demanding in a context where the information available continues to increase exponentially. Investments in the Virtual Physiological Human (VPH) research are largely motivated by the need for integration in healthcare. As all health information becomes digital, the complexity of health care will continue to evolve, translating into an ever increasing pressure which will result from a growing demand in parallel to limited budgets. Hence, the best way to achieve the dream of personalised, preventive, and participative medicine at sustainable costs will be through the integration of all available data, information and knowledge

First Elements on Knowledge Discovery guided by Domain Knowledge (KDDK)

International audienceIn this paper, we present research trends carried out in the Orpailleur team at Loria, showing how knowledge discovery and knowledge processing may be combined. The knowledge discovery in databases process (KDD) consists in processing a huge volume of data for extracting significant and reusable knowledge units. From a knowledge representation perspective, the KDD process may take advantage of domain knowledge embedded in ontologies relative to the domain of data, leading to the notion of ''knowledge discovery guided by domain knowledge'' or KDDK. The KDDK process is based on the classification process (and its multiple forms), e.g. for modeling, representing, reasoning, and discovering. Some applications are detailed, showing how KDDK can be instantiated in an application domain. Finally, an architecture of an integrated KDDK system is proposed and discussed