Structured computer-based training in the interpretation of neuroradiological images

Computer-based systems may be able to address a recognised need throughout the medical profession for a more structured approach to training. We describe a combined training system for neuroradiology, the MR Tutor that differs from previous approaches to computer-assisted training in radiology in that it provides case-based tuition whereby the system and user communicate in terms of a well-founded Image Description Language. The system implements a novel method of visualisation and interaction with a library of fully described cases utilising statistical models of similarity, typicality and disease categorisation of cases. We describe the rationale, knowledge representation and design of the system, and provide a formative evaluation of its usability and effectiveness

Factors associated with the performance and cost-effectiveness of using lymphatic filariasis transmission assessment surveys for monitoring soil-transmitted helminths: a case study in Kenya.

Transmission assessment surveys (TAS) for lymphatic filariasis have been proposed as a platform to assess the impact of mass drug administration (MDA) on soil-transmitted helminths (STHs). This study used computer simulation and field data from pre- and post-MDA settings across Kenya to evaluate the performance and cost-effectiveness of the TAS design for STH assessment compared with alternative survey designs. Variations in the TAS design and different sample sizes and diagnostic methods were also evaluated. The district-level TAS design correctly classified more districts compared with standard STH designs in pre-MDA settings. Aggregating districts into larger evaluation units in a TAS design decreased performance, whereas age group sampled and sample size had minimal impact. The low diagnostic sensitivity of Kato-Katz and mini-FLOTAC methods was found to increase misclassification. We recommend using a district-level TAS among children 8-10 years of age to assess STH but suggest that key consideration is given to evaluation unit size

Promoting Handwashing and Sanitation Behaviour Change in Low- and Middle-Income Countries: A Mixed-Method Systematic Review

This systematic review shows which promotional approaches are effective in changing handwashing and sanitation behaviour and which implementation factors affect the success or failure of such interventions. The authors find that promotional approaches can be effective in terms of handwashing with soap, latrine use, safe faeces disposal and open defecation. No one specific approach is most effective. However, several promotional elements do induce behaviour change. Different barriers and facilitators that influence implementing promotional approaches should be carefully considered when developing new policy, programming, practice, or research in this area

A cell outage management framework for dense heterogeneous networks

In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes-a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., k-nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner

Brain structure in pediatric Tourette syndrome

Previous studies of brain structure in Tourette syndrome (TS) have produced mixed results, and most had modest sample sizes. In the present multicenter study, we used structural magnetic resonance imaging (MRI) to compare 103 children and adolescents with TS to a well-matched group of 103 children without tics. We applied voxel-based morphometry methods to test gray matter (GM) and white matter (WM) volume differences between diagnostic groups, accounting for MRI scanner and sequence, age, sex and total GM+WM volume. The TS group demonstrated lower WM volume bilaterally in orbital and medial prefrontal cortex, and greater GM volume in posterior thalamus, hypothalamus and midbrain. These results demonstrate evidence for abnormal brain structure in children and youth with TS, consistent with and extending previous findings, and they point to new target regions and avenues of study in TS. For example, as orbital cortex is reciprocally connected with hypothalamus, structural abnormalities in these regions may relate to abnormal decision making, reinforcement learning or somatic processing in TS

A Detailed Investigation into Low-Level Feature Detection in Spectrogram Images

Being the first stage of analysis within an image, low-level feature detection is a crucial step in the image analysis process and, as such, deserves suitable attention. This paper presents a systematic investigation into low-level feature detection in spectrogram images. The result of which is the identification of frequency tracks. Analysis of the literature identifies different strategies for accomplishing low-level feature detection. Nevertheless, the advantages and disadvantages of each are not explicitly investigated. Three model-based detection strategies are outlined, each extracting an increasing amount of information from the spectrogram, and, through ROC analysis, it is shown that at increasing levels of extraction the detection rates increase. Nevertheless, further investigation suggests that model-based detection has a limitation—it is not computationally feasible to fully evaluate the model of even a simple sinusoidal track. Therefore, alternative approaches, such as dimensionality reduction, are investigated to reduce the complex search space. It is shown that, if carefully selected, these techniques can approach the detection rates of model-based strategies that perform the same level of information extraction. The implementations used to derive the results presented within this paper are available online from http://stdetect.googlecode.com