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.

Technique for evaluating photo sharing interfaces with the early prototypes - group simulation

User evaluations using paper prototypes commonly lack social context. The Group simulation technique described in this paper offers a solution to this problem. The study introduces an early-phase participatory design technique targeted for small groups. The proposed technique is used for evaluating an interface, which enables group work in photo collection creation. Three groups of four users, 12 in total, took part in a simulation session where they tested a low-fidelity design concept that included their own personal photo content from an event that their group attended together. The users’ own content was used to evoke natural experiences. Our results indicate that the technique helped users to naturally engage with the prototype in the session. The technique is suggested to be suitable for evaluating other early-phase concepts and to guide design solutions, especially with the concepts that include users’ personal content and enable content sharing.

Producing while consuming: Social interaction around photos shared within private group

User-generated content plays a pivotal role in the current social media. The main focus, however, has been on the explicitly generated user content such as photos, videos and status updates on different social networking sites. In this paper, we explore the potential of implicitly generated user content, based on users’ online consumption behaviors. It is technically feasible to record users’ consumption behaviors on mobile devices and share that with relevant people. Mobile devices with such capabilities could enrich social interactions around the consumed content, but it may also threaten users’ privacy. To understand the potentials of this design direction we created and evaluated a low-fidelity prototype intended for photo sharing within private groups. Our prototype incorporates two design concepts, namely, FingerPrint and MoodPhotos that leverage users’ consumption history and emotional responses. In this paper, we report user values and user acceptance of this prototype from three participatory design workshops.

Assessing the immediate and short-term impact of flooding on residential property participant behaviour

The past decade has seen an increase in the number of significant natural disasters that have caused considerable loss of life as well as damage to all property markets in the affected areas. In many cases, these natural disasters have not only caused significant property damage, but in numerous cases, have resulted in the total destruction of the property in the location. With these disasters attracting considerable media attention, the public are more aware of where these affected property markets are, as well as the overall damage to properties that have been damaged or destroyed. This heightened level of awareness has to have an impact on the participants in the property market, whether a developer, vendor seller or investor. To assess this issue, a residential property market that has been affected by a significant natural disaster over the past 2 years has been analysed to determine the overall impact of the disaster on buyer, renter and vendor behaviour, as well as prices in these residential markets. This paper is based on data from the Brisbane flood in January 2011. This natural disaster resulted in loss of life and partial and total devastation of considerable residential property sectors. Data for the research have been based on the residential sales and rental listings for each week of the study period to determine the level of activity in the specific property sectors, and these are also compared to the median house prices for the various suburbs for the same period based on suburbs being either flood affected or flood free. As there are 48 suburbs included in the study, it has been possible to group these suburbs on a socio-economic basis to determine possible differences due to location and value. Data were accessed from realestate.com.au, a free real estate site that provides details of current rental and sales listings on a suburb basis, RP Data a commercial property sales database and the Australian Bureau of Statistics. The paper found that sales listings fell immediately after the flood in the affected areas, but there was no corresponding fall or increase in sales listings in the flood-free suburbs. There was a significant decrease in the number of rental listings follow the flood as affected parties sought alternate accommodation. The greatest fall in rental listings was in areas close to the flood-affected suburbs indicating the desire to be close to the flooded property during the repair period.

A Cyber-Physical System Simulator for risk-free transport studies

The article introduces a novel platform for conducting controlled and risk-free driving and traveling behavior studies, called Cyber-Physical System Simulator (CPSS). The key features of CPSS are: (1) simulation of multiuser immersive driving in a threedimensional (3D) virtual environment; (2) integration of traffic and communication simulators with human driving based on dedicated middleware; and (3) accessibility of multiuser driving simulator on popular software and hardware platforms. This combination of features allows us to easily collect large-scale data on interesting phenomena regarding the interaction between multiple user drivers, which is not possible with current single-user driving simulators. The core original contribution of this article is threefold: (1) we introduce a multiuser driving simulator based on DiVE, our original massively multiuser networked 3D virtual environment; (2) we introduce OpenV2X, a middleware for simulating vehicle-to-vehicle and vehicle to infrastructure communication; and (3) we present two experiments based on our CPSS platform. The first experiment investigates the “rubbernecking” phenomenon, where a platoon of four user drivers experiences an accident in the oncoming direction of traffic. Second, we report on a pilot study about the effectiveness of a Cooperative Intelligent Transport Systems advisory system.

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.

Reactions of simple and peptidic alpha-carboxylate radical anions with dioxygen in the gas phase

alpha-Carboxylate radical anions are potential reactive intermediates in the free radical oxidation of biological molecules (e. g., fatty acids, peptides and proteins). We have synthesised well-defined alpha-carboxylate radical anions in the gas phase by UV laser photolysis of halogenated precursors in an ion-trap mass spectrometer. Reactions of isolated acetate ((center dot)CH(2)CO(2)) and 1-carboxylatobutyl (CH(3)CH(2)CH(2)(center dot)CHCO(2)(-)) radical anions with dioxygen yield carbonate (CO(3)(center dot-)) radical anions and this chemistry is shown to be a hallmark of oxidation in simple and alkyl-substituted cross-conjugated species. Previous solution phase studies have shown that C(alpha)-radicals in peptides, formed from free radical damage, combine with dioxygen to form peroxyl radicals that subsequently decompose into imine and keto acid products. Here, we demonstrate that a novel alternative pathway exists for two alpha-carboxylate C(alpha)-radical anions: the acetylglycinate radical anion (CH(3)C(O)NH(center dot)CHCO(2)(-)) and the model peptide radical anion, YGGFG(center dot-). Reaction of these radical anions with dioxygen results in concerted loss of carbon dioxide and hydroxyl radical. The reaction of the acetylglycinate radical anion with dioxygen reveals a two-stage process involving a slow, followed by a fast kinetic regime. Computational modelling suggests the reversible formation of the C(alpha) peroxyl radical facilitates proton transfer from the amide to the carboxylate group, a process reminiscent of, but distinctive from, classical proton-transfer catalysis. Interestingly, inclusion of this isomerization step in the RRKM/ME modelling of a G3SX level potential energy surface enables recapitulation of the experimentally observed two-stage kinetics.

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.

An efficient scheme of common secure indices for conjunctive keyword-based retrieval on encrypted data

We consider the following problem: members in a dynamic group retrieve their encrypted data from an untrusted server based on keywords and without any loss of data confidentiality and member’s privacy. In this paper, we investigate common secure indices for conjunctive keyword-based retrieval over encrypted data, and construct an efficient scheme from Wang et al. dynamic accumulator, Nyberg combinatorial accumulator and Kiayias et al. public-key encryption system. The proposed scheme is trapdoorless and keyword-field free. The security is proved under the random oracle, decisional composite residuosity and extended strong RSA assumptions.

The comparative behaviour of two combat boots under impact

Background Improvised explosive devices have become the characteristic weapon of conflicts in Iraq and Afghanistan. While little can be done to mitigate against the effects of blast in free-field explosions, scaled blast simulations have shown that the combat boot can attenuate the effects on the vehicle occupants of anti-vehicular mine blasts. Although the combat boot offers some protection to the lower limb, its behaviour at the energies seen in anti-vehicular mine blast has not been documented previously. Methods The sole of eight same-size combat boots from two brands currently used by UK troops deployed to Iraq and Afghanistan were impacted at energies of up to 518 J, using a spring-assisted drop rig. Results The results showed that the Meindl Desert Fox combat boot consistently experienced a lower peak force at lower impact energies and a longer time-to-peak force at higher impact energies when compared with the Lowa Desert Fox combat boot. Discussion This reduction in the peak force and extended rise time, resulting in a lower energy transfer rate, is a potentially positive mitigating effect in terms of the trauma experienced by the lower limb. Conclusion Currently, combat boots are tested under impact at the energies seen during heel strike in running. Through the identification of significantly different behaviours at high loading, this study has shown that there is rationale in adding the performance of combat boots under impact at energies above those set out in international standards to the list of criteria for the selection of a combat boot.

Free-riding, cooperation, and 'peaceful revolutions' in copyright

Modern copyright law is based on the inescapable assumption that users, given the choice, will free-ride rather than pay for access. In fact, many consumers of cultural works – music, books, films, games, and other works – fundamentally want to support their production. It turns out that humans are motivated to support cultural production not only by extrinsic incentives, but also by social norms of fairness and reciprocity. This article explains how producers across the creative industries have used this insight to develop increasingly sophisticated business models that rely on voluntary payments (including pay-what-you-want schemes) to fund their costs of production. The recognition that users are not always free-riders suggests that current policy approaches to copyright are fundamentally flawed. Because social norms are so important in consumer motivations, the perceived unfairness of the current copyright system undermines the willingness of people to pay for access to cultural goods. While recent copyright reform debate has focused on creating stronger deterrence through enforcement, increasing the perceived fairness and legitimacy of copyright law is likely to be much more effective. The fact that users will sometimes willingly support cultural production also challenges the economic raison d'être of copyright law. This article demonstrates how 'peaceful revolutions' are flipping conventional copyright models and encouraging free-riding through combining incentives and prosocial norms. Because they provide a means to support production without limiting the dissemination of knowledge and culture, there is good reason to believe that these commons-based systems of cultural production can be more efficient, more fair, and more conducive to human flourishing than conventional copyright systems. This article explains what we know about free-riding so far and what work remains to be done to understand the viability and importance of cooperative systems in funding cultural production.

Professional development workshop on group work

A professional development toolkit was developed with an agenda, work sheets and resources to support a review of assessment practices pertaining to group work in a first year undergraduate course. A main contribution is the Rational for Group Work in Higher Education template that allows academic staff to determine the purpose for group work and identify the rationale behind the assessment tasks.

Mass spectrometric study of the dissociation of Group XI metal complexes with fatty acids and glycerolipids : Ag2H+ and Cu2H+ ion formation in the presence of a double bond

Results of mass spectrometric studies are reported for the collisional dissociation of Group XI (Cu, Ag, Au) metal ion complexes with fatty acids (palmitic, oleic, linoleic and a-linolenic) and glycerolipids. Remarkably, the formation of M2H+ ions (M = Cu, Ag) is observed as a dissociation product of the ion complexes containing more than one metal cation and only if the lipid in the complex contains a double bond. Ag2H+ is formed as the main dissociation channel for all three of the fatty acids containing double bonds that were investigated while Cu2H+ is formed with one of the fatty acids and, although abundant, is not the dominant dissociation channel. Also. Cu(I) and Ag(I) ion complexes were observed with glycerolipids (including triacylglycerols and glycerophospholipids) containing either saturated or unsaturated fatty acid substituents. Interestingly. Ag2H+ ion is formed in a major fragmentation channel with the lipids that are able to form the complex with two metal cations (triacylglycerols and glycerophosphoglycerols), while lipids containing a fixed positive charge (glycerophospocholines) complex only with a single metal cation. The formation of Ag2H+ ion is a significant dissociation channel from the complex ion Ag-2(L-H)(+) where L = Glycerophospholipid (GP) (18:1/18:1). Cu(I) also forms complexes of two metal cations with glycerophospholipids but these do not produce Cu2H+ upon dissociation. Rather organic fragments, not containing Cu(I), are formed, perhaps due to different interactions of these metal cations with lipids resulting from the much smaller ionic radius of Cu(I) compared to Ag(I) (C).