A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

OWL‐based acquisition and editing of computer‐interpretable guidelines with the CompGuide editor

Computer‐Interpretable Guidelines (CIGs) are the dominant medium for the delivery of clinical decision support, given the evidence‐based nature of their source material. Therefore, these machine‐readable versions have the ability to improve practitioner performance and conformance to standards, with availability at the point and time of care. The formalisation of Clinical Practice Guideline knowledge in a machine‐readable format is a crucial task to make it suitable for the integration in Clinical Decision Support Systems. However, the current tools for this purpose reveal shortcomings with respect to their ease of use and the support offered during CIG acquisition and editing. In this work, we characterise the current landscape of CIG acquisition tools based on the properties of guideline visualisation, organisation, simplicity, automation, manipulation of knowledge elements, and guideline storage and dissemination. Additionally, we describe the CompGuide Editor, a tool for the acquisition of CIGs in the CompGuide model for Clinical Practice Guidelines that also allows the editing of previously encoded guidelines. The Editor guides the users throughout the process of guideline encoding and does not require proficiency in any programming language. The features of the CIG encoding process are revealed through a comparison with already established tools for CIG acquisition.     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data

This research is concerned with the problem of 4 degrees of freedom (DOF) ship manoeuvring identification modelling with the full-scale trial data. To avoid the multi-innovation matrix inversion in the conventional multi-innovation least squares (MILS) algorithm, a new transformed multi-innovation least squares (TMILS) algorithm is first developed by virtue of the coupling identification concept. And much effort is made to guarantee the uniformly ultimate convergence. Furthermore, the auto-constructed TMILS scheme is derived for the ship manoeuvring motion identification by combination with a statistic index. Comparing with the existing results, the proposed scheme has the significant computational advantage and is able to estimate the model structure. The illustrative examples demonstrate the effectiveness of the proposed algorithm, especially including the identification application with full-scale trial data.     

化妆品功效评价(Ⅵ)——化妆品人体功效评价的实验设计

概述了化妆品人体功效评价实验设计的概念、基本要素和基本原则,介绍了常用实验设计类型和实验设计要点,提供了人体功效评价实验方案设计的思路,有助于提高研究者制定实验设计方案的水平。     

Sleep Disorders Reduce Health-Related Quality of Life in Multiple Sclerosis (Nottingham Health Profile Data in Patients with Multiple Sclerosis)

Quality of Life (QoL) is decreased in multiple sclerosis (MS), but studies about the impact of sleep disorders (SD) on health-related quality of Life (HRQoL) are lacking. From our original cohort, a cross-sectional polysomnographic (PSG) study in consecutive MS patients, we retrospectively analysed the previously unpublished data of the Nottingham Health Profile (NHP). Those MS patients suffering from sleep disorders (n = 49) showed significantly lower HRQoL compared to MS patients without sleep disorders (n = 17). Subsequently, we classified the patients into four subgroups: insomnia (n = 17), restless-legs syndrome, periodic limb movement disorder and SD due to leg pain (n = 24), obstructive sleep apnea (n = 8) and patients without sleep disorder (n = 17). OSA and insomnia patients showed significantly higher NHP values and decreased HRQoL not only for the sleep subscale but also for the “energy” and “emotional” area of the NHP. In addition, OSA patients also showed increased NHP values in the “physical abilities” area. Interestingly, we did not find a correlation between the objective PSG parameters and the subjective sleep items of the NHP. However, this study demonstrates that sleep disorders can reduce HRQoL in MS patients and should be considered as an important confounder in all studies investigating HRQoL in MS.     

Group sequential crossover trial designs with strong control of the familywise error rate

Crossover designs are an extremely useful tool to investigators, and group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have rarely been paired together. One possible explanation for this could be the absence of a formal proof of how to strongly control the familywise error rate in the case when multiple comparisons will be made. Here, we provide this proof, valid for any number of initial experimental treatments and any number of stages, when results are analyzed using a linear mixed model. We then establish formulae for the expected sample size and expected number of observations of such a trial, given any choice of stopping boundaries. Finally, utilizing the four-treatment, four-period TOMADO trial as an example, we demonstrate that group sequential methods in this setting could have reduced the trials expected number of observations under the global null hypothesis by over 33%.     

Unresolved controversies concerning psychopathy: Implications for clinical and forensic decision making.

At some point in their careers, clinicians who work or consult in forensic and correctional settings will almost certainly encounter individuals who exhibit psychopathic personality features. Because of the widespread use of this disorder to inform legal and clinical decision making, psychologists should be exceedingly familiar with the relevant research literature on this topic before venturing into these settings. This article reviews the empirical bases of several clinically relevant claims and assertions regarding psychopathy and concludes that many areas of research are decidedly more equivocal in their findings than is commonly perceived. Although there is much to be gained by assessing psychopathy in various contexts, clinicians need to be cautious about drawing overzealous and empirically questionable conclusions about an important disorder that also has great potential for abuse. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Attentional Biases for Negative Interpersonal Stimuli in Clinical Depression.

An information-processing paradigm was used to examine attentional biases in clinically depressed participants, participants with generalized anxiety disorder (GAD), and nonpsychiatric control participants for faces expressing sadness, anger, and happiness. Faces were presented for 1,000 ms, at which point depressed participants had directed their attention selectively to depression-relevant (i.e., sad) faces. This attentional bias was specific to the emotion of sadness; the depressed participants did not exhibit attentional biases to the angry or happy faces. This bias was also specific to depression; at 1,000 ms, participants with GAD were not attending selectively to sad, happy, or anxiety-relevant (i.e., angry) faces. Implications of these findings for both the cognitive and the interpersonal functioning of depressed individuals are discussed and directions for future research are advanced. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Juvenile competence to stand trial evaluations: A survey of current practices and test usage among psychologists.

What is the current standard of practice for evaluations of juvenile competence to stand trial (JCST)? The present study surveyed psychologists regarding the practices used when conducting JCST evaluations. Respondents rated the importance of 17 elements that might be included in a JCST evaluation report. Of these elements, 7 were considered essential by 70% or more of respondents, with 9 additional elements rated as either essential or recommended. A majority of respondents felt that the use of psychological and forensic instruments was important. A list of tests used is provided, and the implications for the development of standards and policy are discussed to provide practitioners with additional knowledge that will help to further the state of the discipline. (PsycINFO Database Record (c) 2010 APA, all rights reserved)