Ventilation rates in schools and pupil’s performance using computerized assessment tests

Research shows that poor indoor air quality (IAQ) in school buildings can cause a reduction in the students’ performance assessed by short-term computer-based tests; whereas good air quality in classrooms can enhance children's concentration and also teachers’ productivity. Investigation of air quality in classrooms helps us to characterise pollutant levels and implement corrective measures. Outdoor pollution, ventilation equipment, furnishings, and human activities affect IAQ. In school classrooms, the occupancy density is high (1.8–2.4 m2/person) compared to offices (10 m2/person). Ventilation systems expend energy and there is a trend to save energy by reducing ventilation rates. We need to establish the minimum acceptable level of fresh air required for the health of the occupants. This paper describes a project, which will aim to investigate the effect of IAQ and ventilation rates on pupils’ performance and health using psychological tests. The aim is to recommend suitable ventilation rates for classrooms and examine the suitability of the air quality guidelines for classrooms. The air quality, ventilation rates and pupils’ performance in classrooms will be evaluated in parallel measurements. In addition, Visual Analogue Scales will be used to assess subjective perception of the classroom environment and SBS symptoms. Pupil performance will be measured with Computerised Assessment Tests (CAT), and Pen and Paper Performance Tasks while physical parameters of the classroom environment will be recorded using an advanced data logging system. A total number of 20 primary schools in the Reading area are expected to participate in the present investigation, and the pupils participating in this study will be within the age group of 9–11 years. On completion of the project, based on the overall data recommendations for suitable ventilation rates for schools will be formulated.

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Assessing the accuracy of a computerized decision support system for digoxin dosing in primary care: an observational study

Background: This study was carried out as part of a European Union funded project (PharmDIS-e+), to develop and evaluate software aimed at assisting physicians with drug dosing. A drug that causes particular problems with drug dosing in primary care is digoxin because of its narrow therapeutic range and low therapeutic index. Objectives: To determine (i) accuracy of the PharmDIS-e+ software for predicting serum digoxin levels in patients who are taking this drug regularly; (ii) whether there are statistically significant differences between predicted digoxin levels and those measured by a laboratory and (iii) whether there are differences between doses prescribed by general practitioners and those suggested by the program. Methods: We needed 45 patients to have 95% Power to reject the null hypothesis that the mean serum digoxin concentration was within 10% of the mean predicted digoxin concentration. Patients were recruited from two general practices and had been taking digoxin for at least 4 months. Exclusion criteria were dementia, low adherence to digoxin and use of other medications known to interact to a clinically important extent with digoxin. Results: Forty-five patients were recruited. There was a correlation of 0·65 between measured and predicted digoxin concentrations (P < 0·001). The mean difference was 0·12 μg/L (SD 0·26; 95% CI 0·04, 0·19, P = 0·005). Forty-seven per cent of the patients were prescribed the same dose as recommended by the software, 44% were prescribed a higher dose and 9% a lower dose than recommended. Conclusion: PharmDIS-e+ software was able to predict serum digoxin levels with acceptable accuracy in most patients.

Computerized short-term memory treatment for older adults with aphasia

We report on a software prototype designed to deliver a novel term memory treatment for older adults with aphasia. We conducted a review of the prototype with 14 speech and language therapists, to elicit feedback on the potential usefulness of the ultimate application and, particularly, the prototype in terms of its main design features and use by older adults with aphasia. The clinicians’ feedback highlights a number of design considerations relating to the usability, training methods, and appeal of treatment software, which can help engage patients more fully in computerized treatments and improve treatment outcomes.

Smart-phone based electrocardiogram wavelet decomposition and neural network classification

This paper discusses ECG classification after parametrizing the ECG waveforms in the wavelet domain. The aim of the work is to develop an accurate classification algorithm that can be used to diagnose cardiac beat abnormalities detected using a mobile platform such as smart-phones. Continuous time recurrent neural network classifiers are considered for this task. Records from the European ST-T Database are decomposed in the wavelet domain using discrete wavelet transform (DWT) filter banks and the resulting DWT coefficients are filtered and used as inputs for training the neural network classifier. Advantages of the proposed methodology are the reduced memory requirement for the signals which is of relevance to mobile applications as well as an improvement in the ability of the neural network in its generalization ability due to the more parsimonious representation of the signal to its inputs.

Cone-beam computerized tomographic, radiographic, and histologic evaluation of periapical repair in dogs` post-endodontic treatment

Objective. To evaluate the periapical repair after root canal treatment in the teeth of dogs using CT and conventional radiography and to compare these findings with the gold standard microscopic evaluation. Study design. The animals were divided into three groups according to endodontic treatment performed: Group 1, single-visit endodontic treatment in teeth without apical periodontitis; Group 2, single-visit endodontic treatment in teeth with apical periodontitis; and Group 3, endodontic treatment in teeth with apical periodontitis using calcium hydroxide as a root canal dressing. Group 4 consisted of teeth with apical periodontitis not submitted to root canal treatment and Group 5 consisted of healthy teeth without periapical disease. Radiographic, tomographic, and microscopic evaluations were performed by blind examiners. At 180 days experimental time, CT and radiographic measurements of periapical disease were compared with the gold standard microscopic measurement using intraclass correlation coefficient. Intergroup comparisons considering different methods of periapical lesions measurement or different clinical protocols of root canal treatment were performed by Kruskal Wallis test followed by Dunn. Integrity of lamina dura, presence of radiolucent areas, and presence of root resorption were analyzed by Fisher`s exact test. Results. There was discontinuity of the lamina dura and CPD in all teeth from Groups 2, 3, and 4 evaluated by tomography and radiography 45 days after CPD induction. Radiographically, 180 days after root canal treatment, there was no periapical lesion in teeth from Groups 1 and 3, different from groups 2 and 4 (p < .05). The highest reduction in the CPD size was observed on Group 3 (p < .05). According to the tomographic results, there was decrease of the size of the CPD on Group 3 but not on Groups 2 or 4. However, in all groups the periapical lesions presented larger mesio-distal extension if compared with radiography, both 45 days after CPD induction and 180 days after root canal treatment. At 180 days, CT measurements were closely related to microscopic results (ICC = 0.95) differently from radiographic evaluation (ICC = 0.86). Conclusion. CT Scan evaluation of periapical repair following root canal treatment provided similar information than that obtained by microscopic analysis, whereas radiographic evaluation underestimated the size do periapical lesion. (Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2009; 108:796-805)

Computerized identification of motor complications in Parkinson's disease

Objective: To investigate whether spirography-based objective measures are able to effectively characterize the severity of unwanted symptom states (Off and dyskinesia) and discriminate them from motor state of healthy elderly subjects. Background: Sixty-five patients with advanced Parkinson’s disease (PD) and 10 healthy elderly (HE) subjects performed repeated assessments of spirography, using a touch screen telemetry device in their home environments. On inclusion, the patients were either treated with levodopa-carbidopa intestinal gel or were candidates for switching to this treatment. On each test occasion, the subjects were asked trace a pre-drawn Archimedes spiral shown on the screen, using an ergonomic pen stylus. The test was repeated three times and was performed using dominant hand. A clinician used a web interface which animated the spiral drawings, allowing him to observe different kinematic features, like accelerations and spatial changes, during the drawing process and to rate different motor impairments. Initially, the motor impairments of drawing speed, irregularity and hesitation were rated on a 0 (normal) to 4 (extremely severe) scales followed by marking the momentary motor state of the patient into 2 categories that is Off and Dyskinesia. A sample of spirals drawn by HE subjects was randomly selected and used in subsequent analysis. Methods: The raw spiral data, consisting of stylus position and timestamp, were processed using time series analysis techniques like discrete wavelet transform, approximate entropy and dynamic time warping in order to extract 13 quantitative measures for representing meaningful motor impairment information. A principal component analysis (PCA) was used to reduce the dimensions of the quantitative measures into 4 principal components (PC). In order to classify the motor states into 3 categories that is Off, HE and dyskinesia, a logistic regression model was used as a classifier to map the 4 PCs to the corresponding clinically assigned motor state categories. A stratified 10-fold cross-validation (also known as rotation estimation) was applied to assess the generalization ability of the logistic regression classifier to future independent data sets. To investigate mean differences of the 4 PCs across the three categories, a one-way ANOVA test followed by Tukey multiple comparisons was used. Results: The agreements between computed and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91. The mean PC scores were different across the three motor state categories, only at different levels. The first 2 PCs were good at discriminating between the motor states whereas the PC3 was good at discriminating between HE subjects and PD patients. The mean scores of PC4 showed a trend across the three states but without significant differences. The Spearman’s rank correlations between the first 2 PCs and clinically assessed motor impairments were as follows: drawing speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17), and hesitation (PC1, 0.27; PC2, 0.77). Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits and can be used to distinguish drug-related motor dysfunctions between Off and dyskinesia in PD. These measures can be potentially useful during clinical evaluation of individualized drug-related complications such as over- and under-medications thus maximizing the amount of time the patients spend in the On state.

Evaluation of the usefulness of 'Marvin'; a computerized assessment tool for investigative interviewers of children

This study examined the usefulness of a computerized developmental assessment tool, designed to provide investigative interviewers with knowledge about children's understanding of spatial, temporal, numerical, and color terms that may be relevant to the forensic setting. Specifically, the effect of the computer program (compared to a standard verbal and no assessment) was examined on 4- to 5-year-old children's recall of an independent event and their enjoyment of the interview process. In addition, children's performance on the computerized and verbal developmental assessment was compared with their performance when recalling the independent event. Overall, the children rated the assessment conducted on computer more favorably than the verbal assessment. Further, the verbal assessment elicited responses that were more consistent with their responses about the event than the computerized assessment. However, there was no difference in the accuracy and detail of children's responses about the independent event, irrespective of whether the children received the computerized or verbal assessment, or no assessment. Directions for future research are discussed.

A method for tracking rats in a complex and completely dark environment using computerized video analysis

The automated tracking of rodents in open field environments has become a standard laboratory technique for the investigation of the effects of drugs, novel therapeutic interventions and genetic mutations on behavior. Here, we develop an extension of this technique that permits tracking in full darkness through a complex (‘enriched’) environment comprising naturalistic structures such as tunnels and hides. To eliminate unwanted light reflections and tape noise, we developed a unique video filter that combines the advantages of differential and non-differential filtering. This filter enabled the tracking of albino rats against a relatively dark background to an accuracy of approximately 97% compared to hand tracking of the same animal, irrespective of whether the rat was inside a hide box or tunnel or out in the open field. The system as a whole can be easily deployed using standard PCs and inexpensive infrared cameras and lights.

A computerized method for objective measurement of muscle tone

This article is concentrated on the objective computerizing method of measuring of muscle tone using compressive and decompressive deformation of superficial skeletal muscle of wrist in vivo. Four indices were highly recommended for complex analysis of muscle tone.

A new computerized adaptive test advancing the measurement of health-related quality of life (HRQoL) in children: the Kids-CAT

Purpose: Assessing health-related quality of life (HRQoL) via Computerized Adaptive Tests (CAT) provides greater measurement precision coupled with a lower test burden compared to conventional tests. Currently, there are no European pediatric HRQoL CATs available. This manuscript aims at describing the development of a HRQoL CAT for children and adolescents: the Kids-CAT, which was developed based on the established KIDSCREEN-27 HRQoL domain structure. Methods: The Kids-CAT was developed combining classical test theory and item response theory methods and using large archival data of European KIDSCREEN norm studies (n = 10,577–19,580). Methods were applied in line with the US PROMIS project. Item bank development included the investigation of unidimensionality, local independence, exploration of Differential Item Functioning (DIF), evaluation of Item Response Curves (IRCs), estimation and norming of item parameters as well as first CAT simulations. Results: The Kids-CAT was successfully built covering five item banks (with 26–46 items each) to measure physical well-being, psychological well-being, parent relations, social support and peers, and school well-being. The Kids-CAT item banks proved excellent psychometric properties: high content validity, unidimensionality, local independence, low DIF, and model conform IRCs. In CAT simulations, seven items were needed to achieve a measurement precision between.8 and.9 (reliability). It has a child-friendly design, is easy accessible online and gives immediate feedback reports of scores. Conclusions: The Kids-CAT has the potential to advance pediatric HRQoL measurement by making it less burdensome and enhancing the patient–doctor communication.

Erratum to: A new computerized adaptive test advancing the measurement of health-related quality of life (HRQoL) in children: the Kids-CAT

Abstract
Purpose
Assessing health-related quality of life (HRQoL) via Computerized Adaptive Tests (CAT) provides greater measurement precision coupled with a lower test burden compared to conventional tests. Currently, there are no European pediatric HRQoL CATs available. This manuscript aims at describing the development of a HRQoL CAT for children and adolescents: the Kids-CAT, which was developed based on the established KIDSCREEN-27 HRQoL domain structure.
Methods
The Kids-CAT was developed combining classical test theory and item response theory methods and using large archival data of European KIDSCREEN norm studies (n=10,577–19,580). Methods were applied in line with the US PROMIS project. Item bank development included the investigation of unidimensionality, local independence, exploration of Differential Item Functioning (DIF), evaluation of Item Response Curves (IRCs), estimation and norming of item parameters as well as first CAT simulations.
Results
The Kids-CAT was successfully built covering five item banks (with 26–46 items each) to measure physical well-being, psychological well-being, parent relations, social support and peers, and school well-being. The Kids-CAT item banks proved excellent psychometric properties: high content validity, unidimensionality, local independence, low DIF, and model conform IRCs. In CAT simulations, seven items were needed to achieve a measurement precision between .8 and .9 (reliability). It has a child-friendly design, is easy accessible online and gives immediate feedback reports of scores.
Conclusions
The Kids-CAT has the potential to advance pediatric HRQoL measurement by making it less burdensome and enhancing the patient–doctor communication.

Nurses' Use of Computerized Clinical Guidelines to Improve Patient Safety in Hospitals.

Computerized clinical guidelines are frequently used to translate research into evidence-based behavioral practices and to improve patient outcomes. The purpose of this integrative review is to summarize the factors influencing nurses' use of computerized clinical guidelines and the effects of nurses' use of computerized clinical guidelines on patient safety improvements in hospitals. The Embase, Medline Complete, and Cochrane databases were searched for relevant literature published from 2000 to January 2013. The matrix method was used, and a total of 16 papers were included in the final review. The studies were assessed for quality with the Critical Appraisal Skills Program. The studies focused on nurses' adherence to guidelines and on improved patient care and patient outcomes as benefits of using computerized clinical guidelines. The nurses' use of computerized clinical guidelines demonstrated improvements in care processes; however, the evidence for an effect of computerized clinical guidelines on patient safety remains limited.

Classification of electrocardiogram and auscultatory blood pressure signals using machine learning models

In this paper, two real-world medical classification problems using electrocardiogram (ECG) and auscultatory blood pressure (Korotkoff) signals are examined. A total of nine machine learning models are applied to perform classification of the medical data sets. A number of useful performance metrics which include accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve are computed. In addition to the original data sets, noisy data sets are generated to evaluate the robustness of the classifiers against noise. The 10-fold cross validation method is used to compute the performance statistics, in order to ensure statistically reliable results pertaining to classification of the ECG and Korotkoff signals are produced. The outcomes indicate that while logistic regression models perform the best with the original data set, ensemble machine learning models achieve good accuracy rates with noisy data sets.