Fuzzy Logic in Clinical Practice Decision Support Systems

Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners

Transferring Your Farm Business to the Next Generation

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Appropriate choice of aggregation operators in fuzzy decision support systems

Fuzzy logic provides a mathematical formalism for a unified treatment of vagueness and imprecision that are ever present in decision support and expert systems in many areas. The choice of aggregation operators is crucial to the behavior of the system that is intended to mimic human decision making. This paper discusses how aggregation operators can be selected and adjusted to fit empirical data&mdash;a series of test cases. Both parametric and nonparametric regression are considered and compared. A practical application of the proposed methods to electronic implementation of clinical guidelines is presented<br /

How to Evaluate Health Applications with Conversational User Interface?

Application of conversational user interfaces (CUI) or chatbots to healthcare is gaining interest fueled by the rising power of artificial intelligence, increasing popularity of mobile health applications and the desire for engagement and usability. While their use is mainly justified by increasing adherence to mobile health applications and facilitating interactions with the system, the question arises: How can such systems be evaluated in a reliable manner? This paper introduces an evaluation framework for health systems whose core interaction principle is a CUI. We derive quality dimensions and attributes by collecting relevant evaluation aspects from applications that have been developed in previous work and from literature on health chatbots. The collected aspects are aggregated into six thematic categories for chatbot quality, including user experience, linguistic, task-oriented and artificial intelligence perspectives, but also healthcare quality and system quality perspectives. The framework is intended to support developers and researchers in the domain of chatbots in healthcare in selecting relevant quality attributes to be assessed before their systems are distributed to patients

Editors Speak Out on Refereeing ; Another kind of Evaluation ; Writing for Professional Publications: Ways to Increase your success.

Reviews of Editors Speak Out on Refereeing, by Bruce M. Smith and Pauline B. Gough; Another Kind of Evaluation, by M.F. Smith and Yvonna S. Lincoln; Writing for Professional Publications: Ways to Increase your Success, by Kenneth T. Henson

Grease (October 10-26, 1980)

Program for Grease (October 10-26, 1980)

Understanding Individual Experiences of Chronic Illness with Semantic Space Models of Electronic Discussions

Electronic discussion groups provide a convenient forum for individuals to share their experiences of chronic illness. The language use of individual participants, and the way their language shifts over time, may provide implicit indications of important shifts in sense-of-self. This paper relates experience with application of the hyperspace analogue to language (HAL) model for automatic construction of a dimensional model from a corpus of text. HAL is applied to 17 months of discussion on a closed list of 20 women coping with chronic illness. The discussion group was moderated for a focus the phenomenon of "Transition' - how people can learn to incorporate the consequences of illness into their lives. The current phase of research focuses on identification of clusters of words that can represent key aspects of Transition. The HAL models for two participants have been analyzed by experts in Transition to form candidate clusters. These clusters are then used as a basis for contrasting the language usage of an individual participant over time as compared to the entire corpus. We have not yet found a reliable basis for identifying transitions in an individual based on their entries into a discussion forum, although the clusters may have some inherent value for introspection on individual experiences and Transition in general. We report challenges for interpretation of the HAL model related to the correlation of dimensions and the impact of group dynamics

Echo of the Past

The story of the controversial spring 1955 issue of Furman\u27s student literary magazine

Laboratory-confirmed respiratory infections as triggers for acute myocardial infarction and stroke: a self-controlled case series analysis of national linked datasets from Scotland

While acute respiratory tract infections can trigger cardiovascular events, the differential effect of specific organisms is unknown. This is important to guide vaccine policy.Using national infection surveillance data linked to the Scottish Morbidity Record, we identified adults with a first myocardial infarction or stroke from January 1, 2004 to December 31, 2014 and a record of laboratory-confirmed respiratory infection during this period. Using self-controlled case series analysis, we generated age- and season-adjusted incidence ratios (IRs) for myocardial infarction (n=1227) or stroke (n=762) after infections compared with baseline time.We found substantially increased myocardial infarction rates in the week after Streptococcus pneumoniae and influenza virus infection: adjusted IRs for days 1-3 were 5.98 (95% CI 2.47-14.4) and 9.80 (95% CI 2.37-40.5), respectively. Rates of stroke after infection were similarly high and remained elevated to 28 days: day 1-3 adjusted IRs 12.3 (95% CI 5.48-27.7) and 7.82 (95% CI 1.07-56.9) for S. pneumoniae and influenza virus, respectively. Although other respiratory viruses were associated with raised point estimates for both outcomes, only the day 4-7 estimate for stroke reached statistical significance.We showed a marked cardiovascular triggering effect of S. pneumoniae and influenza virus, which highlights the need for adequate pneumococcal and influenza vaccine uptake. Further research is needed into vascular effects of noninfluenza respiratory viruses