Clinician-driven automated classification of limb fractures from free-text radiology reports

The aim of this research is to report initial experimental results and evaluation of a clinician-driven automated method that can address the issue of misdiagnosis from unstructured radiology reports. Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to disperse information resources and vast amounts of manual processing of unstructured information, a point-of-care accurate diagnosis is often difficult. A rule-based method that considers the occurrence of clinician specified keywords related to radiological findings was developed to identify limb abnormalities, such as fractures. A dataset containing 99 narrative reports of radiological findings was sourced from a tertiary hospital. The rule-based method achieved an F-measure of 0.80 and an accuracy of 0.80. While our method achieves promising performance, a number of avenues for improvement were identified using advanced natural language processing (NLP) techniques.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

Working knowledge for collaborative water planning in Australia’s Wet Tropics region

Cooperation between multiple environmental decision-makers and activities is necessary to address the impacts of diffuse sources of agricultural pollution on the water quality entering Australia’s Great Barrier Reef (GBR). Water planning efforts requires available knowledge to inform this co-operative water program implementation and reform. This paper uses knowledge sharing, translation and feedback features of collaboration as a way to assess knowledge work practices during key phases of the water planning process. This enabled a systematic review of knowledge work practices in partnership with collaborative water planning groups established to inform water quality program investment decisions in the GBR’s Wet Tropics region. This research builds on the growing academic and policy interest in the conditions required to enable different types of knowledge to be successfully used for policy-making by focusing on when, how and why knowledge work to meet these conditions is required.

Spatially-explicit modelling of grassland classes - an improved method of integrating a climate-based classification model with interpolated climate surfaces

Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.

Heterogeneity of clinical and environmental isolates of Mycobacterium fortuitum using repetitive element sequence-based PCR: municipal water an unlikely source of community-acquired infections

M. fortuitum is a rapidly growing mycobacterium associated with community-acquired and nosocomial wound, soft tissue, and pulmonary infections. It has been postulated that water has been the source of infection especially in the hospital setting. The aim of this study was to determine if municipal water may be the source of community-acquired or nosocomial infections in the Brisbane area. Between 2007 and 2009, 20 strains of M. fortuitum were recovered from municipal water and 53 patients’ isolates were submitted to the reference laboratory. A wide variation in strain types was identified using repetitive element sequence-based PCR, with 13 clusters of ≥2 indistinguishable isolates, and 28 patterns consisting of individual isolates. The clusters could be grouped into seven similar groups (>95% similarity). Municipal water and clinical isolates collected during the same time period and from the same geographical area consisted of different strain types, making municipal water an unlikely source of sporadic human infection.

Strain variation amongst clinical and potable water isolates of M.kansasii using automated repetitive unit PCR

Mycobacterium kansasii is a pulmonary pathogen that has been grown readily from municipal water, but rarely isolated from natural waters. A definitive link between water exposure and disease has not been demonstrated and the environmental niche for this organism is poorly understood. Strain typing of clinical isolates has revealed seven subtypes with Type 1 being highly clonal and responsible for most infections worldwide. The prevalence of other subtypes varies geographically. In this study 49 water isolates are compared with 72 patient isolates from the same geographical area (Brisbane, Australia), using automated repetitive unit PCR (Diversilab) and ITS RFLP. The clonality of the dominant clinical strain type is again demonstrated but with rep-PCR, strain variation within this group is evident comparable with other reported methods. There is significant heterogeneity of water isolates and very few are similar or related to the clinical isolates. This suggests that if water or aerosol transmission is the mode of infection, then point source contamination likely occurs from an alternative environmental source.

Prior storm experience moderates water surge perception and risk

Background How accurately do people perceive extreme water speeds and how does their perception affect perceived risk? Prior research has focused on the characteristics of moving water that can reduce human stability or balance. The current research presents the first experiment on people's perceptions of risk and moving water at different speeds and depths. Methods Using a randomized within-person 2 (water depth: 0.45, 0.90 m) ×3 (water speed: 0.4, 0.8, 1.2 m/s) experiment, we immersed 76 people in moving water and asked them to estimate water speed and the risk they felt. Results Multilevel modeling showed that people increasingly overestimated water speeds as actual water speeds increased or as water depth increased. Water speed perceptions mediated the direct positive relationship between actual water speeds and perceptions of risk; the faster the moving water, the greater the perceived risk. Participants' prior experience with rip currents and tropical cyclones moderated the strength of the actual–perceived water speed relationship; consequently, mediation was stronger for people who had experienced no rip currents or fewer storms. Conclusions These findings provide a clearer understanding of water speed and risk perception, which may help communicate the risks associated with anticipated floods and tropical cyclones.

Supplementary material : large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

IODP Expedition 339 in the Gulf of Cadiz and off West Iberia : decoding the environmental significance of the Mediterranean outflow water and its global influence

IODP Expedition 339 drilled five sites in the Gulf of Cadiz and two off the west Iberian margin (November 2011 to January 2012), and recovered 5.5 km of sediment cores with an average recovery of 86.4%. The Gulf of Cadiz was targeted for drilling as a key location for the investigation of Mediterranean outflow water (MOW) through the Gibraltar Gateway and its influence on global circulation and climate. It is also a prime area for understanding the effects of tectonic activity on evolution of the Gibraltar Gateway and on margin sedimentation. We penetrated into the Miocene at two different sites and established a strong signal of MOW in the sedimentary record of the Gulf of Cadiz, following the opening of the Gibraltar Gateway. Preliminary results show the initiation of contourite deposition at 4.2–4.5 Ma, although subsequent research will establish whether this dates the onset of MOW. The Pliocene succession, penetrated at four sites, shows low bottom current activity linked with a weak MOW. Significant widespread unconformities, present in all sites but with hiatuses of variable duration, are interpreted as a signal of intensified MOW, coupled with flow confinement. The Quaternary succession shows a much more pronounced phase of contourite drift development, with two periods of MOW intensification separated by a widespread unconformity. Following this, the final phase of drift evolution established the contourite depositional system (CDS) architecture we see today. There is a significant climate control on this evolution of MOW and bottom-current activity. However, from the closure of the Atlantic–Mediterranean gateways in Spain and Morocco just over 6 Ma and the opening of the Gibraltar Gateway at 5.3 Ma, there has been an even stronger tectonic control on margin development, downslope sediment transport and contourite drift evolution. The Gulf of Cadiz is the world's premier contourite laboratory and thus presents an ideal testing ground for the contourite paradigm. Further study of these contourites will allow us to resolve outstanding issues related to depositional processes, drift budgets, and recognition of fossil contourites in the ancient record on shore. The expedition also verified an enormous quantity and extensive distribution of contourite sands that are clean and well sorted. These represent a relatively untapped and important exploration target for potential oil and gas reservoirs.

Sustainable Urban Water Environment : Climate, Pollution and Adaptation

"This multi-disciplinary book provides practical solutions for safeguarding the sustainability of the urban water environment. Firstly, the importance of the urban water environment is highlighted and the major problems urban water bodies face and strategies to safeguard the water environment are explored. Secondly, the diversity of pollutants entering the water environment through stormwater runoff are discussed and modelling approaches for factoring in climate change and future urban and transport scenarios are proposed. Thirdly, by linking the concepts of sustainable urban ecosystems and sustainable urban and transport development, capabilities of two urban sustainability assessment models are demonstrated."--publisher website

Setting water quality objectives for the health of freshwater fish

An important responsibility of the Environment Protection Authority, Victoria, is to set objectives for levels of environmental contaminants. To support the development of environmental objectives for water quality, a need has been identified to understand the dual impacts of concentration and duration of a contaminant on biota in freshwater streams. For suspended solids contamination, information reported by Newcombe and Jensen [ North American Journal of Fisheries Management , 16(4):693--727, 1996] study of freshwater fish and the daily suspended solids data from the United States Geological Survey stream monitoring network is utilised. The study group was requested to examine both the utility of the Newcombe and Jensen and the USA data, as well as the formulation of a procedure for use by the Environment Protection Authority Victoria that takes concentration and duration of harmful episodes into account when assessing water quality. The extent to which the impact of a toxic event on fish health could be modelled deterministically was also considered. It was found that concentration and exposure duration were the main compounding factors on the severity of effects of suspended solids on freshwater fish. A protocol for assessing the cumulative effect on fish health and a simple deterministic model, based on the biology of gill harm and recovery, was proposed. References D. W. T. Au, C. A. Pollino, R. S. S Wu, P. K. S. Shin, S. T. F. Lau, and J. Y. M. Tang. Chronic effects of suspended solids on gill structure, osmoregulation, growth, and triiodothyronine in juvenile green grouper epinephelus coioides . Marine Ecology Press Series , 266:255--264, 2004. J.C. Bezdek, S.K. Chuah, and D. Leep. Generalized k-nearest neighbor rules. Fuzzy Sets and Systems , 18:237--26, 1986. E. T. Champagne, K. L. Bett-Garber, A. M. McClung, and C. Bergman. {Sensory characteristics of diverse rice cultivars as influenced by genetic and environmental factors}. Cereal Chem. , {81}:{237--243}, {2004}. S. G. Cheung and P. K. S. Shin. Size effects of suspended particles on gill damage in green-lipped mussel perna viridis. Marine Pollution Bulletin , 51(8--12):801--810, 2005. D. H. Evans. The fish gill: site of action and model for toxic effects of environmental pollutants. Environmental Health Perspectives , 71:44--58, 1987. G. C. Grigg. The failure of oxygen transport in a fish at low levels of ambient oxygen. Comp. Biochem. Physiol. , 29:1253--1257, 1969. G. Holmes, A. Donkin, and I.H. Witten. {Weka: A machine learning workbench}. In Proceedings of the Second Australia and New Zealand Conference on Intelligent Information Systems , volume {24}, pages {357--361}, {Brisbane, Australia}, {1994}. {IEEE Computer Society}. D. D. Macdonald and C. P. Newcombe. Utility of the stress index for predicting suspended sediment effects: response to comments. North American Journal of Fisheries Management , 13:873--876, 1993. C. P. Newcombe. Suspended sediment in aquatic ecosystems: ill effects as a function of concentration and duration of exposure. Technical report, British Columbia Ministry of Environment, Lands and Parks, Habitat Protection branch, Victoria, 1994. C. P. Newcombe and J. O. T. Jensen. Channel suspended sediment and fisheries: A synthesis for quantitative assessment of risk and impact. North American Journal of Fisheries Management , 16(4):693--727, 1996. C. P. Newcombe and D. D. Macdonald. Effects of suspended sediments on aquatic ecosystems. North American Journal of Fisheries Management , 11(1):72--82, 1991. K. Schmidt-Nielsen. Scaling. Why is animal size so important? Cambridge University Press, NY, 1984. J. S. Schwartz, A. Simon, and L. Klimetz. Use of fish functional traits to associate in-stream suspended sediment transport metrics with biological impairment. Environmental Monitoring and Assessment , 179(1--4):347--369, 2011. E. Al Shaw and J. S. Richardson. Direct and indirect effects of sediment pulse duration on stream invertebrate assemb ages and rainbow trout ( Oncorhynchus mykiss ) growth and survival. Canadian Journal of Fish and Aquatic Science , 58:2213--2221, 2001. P. Tiwari and H. Hasegawa. {Demand for housing in Tokyo: A discrete choice analysis}. Regional Studies , {38}:{27--42}, {2004}. Y. Tramblay, A. Saint-Hilaire, T. B. M. J. Ouarda, F. Moatar, and B Hecht. Estimation of local extreme suspended sediment concentrations in california rivers. Science of the Total Environment , 408:4221--

Binary image steganographic techniques classification based on multi-class steganalysis

In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.

Automated classification of limb fractures from free-text radiology reports using a clinician-informed gazetteer methodology

Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.