Classification of cancer-related death certificates using machine learning

Background Cancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities. Aims In this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated. Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes. Results Death certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM) classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032) and false negative rate (0.0297) while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers. Conclusion The selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with an SVM classifier.

Treatment plan complexity metrics for predicting IMRT pre-treatment quality assurance results

The planning of IMRT treatments requires a compromise between dose conformity (complexity) and deliverability. This study investigates established and novel treatment complexity metrics for 122 IMRT beams from prostate treatment plans. The Treatment and Dose Assessor software was used to extract the necessary data from exported treatment plan files and calculate the metrics. For most of the metrics, there was strong overlap between the calculated values for plans that passed and failed their quality assurance (QA) tests. However, statistically significant variation between plans that passed and failed QA measurements was found for the established modulation index and for a novel metric describing the proportion of small apertures in each beam. The ‘small aperture score’ provided threshold values which successfully distinguished deliverable treatment plans from plans that did not pass QA, with a low false negative rate.

The genome of the domesticated apple (Malus × domestica Borkh.)

We report a high-quality draft genome sequence of the domesticated apple (Malus × domestica). We show that a relatively recent (>50 million years ago) genome-wide duplication (GWD) has resulted in the transition from nine ancestral chromosomes to 17 chromosomes in the Pyreae. Traces of older GWDs partly support the monophyly of the ancestral paleohexaploidy of eudicots. Phylogenetic reconstruction of Pyreae and the genus Malus, relative to major Rosaceae taxa, identified the progenitor of the cultivated apple as M. sieversii. Expansion of gene families reported to be involved in fruit development may explain formation of the pome, a Pyreae-specific false fruit that develops by proliferation of the basal part of the sepals, the receptacle. In apple, a subclade of MADS-box genes, normally involved in flower and fruit development, is expanded to include 15 members, as are other gene families involved in Rosaceae-specific metabolism, such as transport and assimilation of sorbitol.

On display : Ravensthorpe Wildflower Show and the assembly of place

Each September since 1983 in the rural Shire of Ravensthorpe, Western Australia, volunteers collect samples of up to 700 wildfl ower species which are then displayed in the Ravensthorpe Senior Citizens Centre from 9.00 am to 4.00 pm daily over a two-week period. This chapter offers an ethnographic interpretation of this enduring annual event focusing on the 25th show held in 2007. The study contributes to understanding the complex and nuanced role of local wildflower shows in shaping and supporting rural senses of place and of community. Importantly, this particular type of festival, and more specifically this local instance, foregrounds a less-remarked aspect of festivals, namely the (re)production and celebration of place-specific knowledge through validations of, and interconnections between, scientific flower classification and emotive experience. This feature, encapsulated in Laurel Lamperd’s poem above, invites consideration of the ways in which local place knowledge and the simultaneous (re)production of ‘place’ are constituted by a complex layering of rational, objective ways of knowing and those which emphasize emotions, aesthetics and memories. This rural wildflower show not only mobilises both the rational and the emotional in ‘making sense of the world’ for local residents and for tourists, but also offers insights into the production of place as constituted in and through relations between humans and non-human life forms (Cloke & Jones, 2001; Conradson, 2005; see also Chapter 6).

Recursive actuator fault detection and diagnosis for emergency landing of UASs

This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.

Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

Intrinsic frames of reference in haptic spatial learning

It has been proposed that spatial reference frames with which object locations are specified in memory are intrinsic to a to-be-remembered spatial layout (intrinsic reference theory). Although this theory has been supported by accumulating evidence, it has only been collected from paradigms in which the entire spatial layout was simultaneously visible to observers. The present study was designed to examine the generality of the theory by investigating whether the geometric structure of a spatial layout (bilateral symmetry) influences selection of spatial reference frames when object locations are sequentially learned through haptic exploration. In two experiments, participants learned the spatial layout solely by touch and performed judgments of relative direction among objects using their spatial memories. Results indicated that the geometric structure can provide a spatial cue for establishing reference frames as long as it is accentuated by explicit instructions (Experiment 1) or alignment with an egocentric orientation (Experiment 2). These results are entirely consistent with those from previous studies in which spatial information was encoded through simultaneous viewing of all object locations, suggesting that the intrinsic reference theory is not specific to a type of spatial memory acquired by the particular learning method but instead generalizes to spatial memories learned through a variety of encoding conditions. In particular, the present findings suggest that spatial memories that follow the intrinsic reference theory function equivalently regardless of the modality in which spatial information is encoded.

Differential effects of aging on spatial learning through exploratory navigation and map reading

It has been shown that abilities in spatial learning and memory are adversely affected by aging. The present study was conducted to investigate whether increasing age has equal consequences for all types of spatial learning or impacts certain types of spatial learning selectively. Specifically, two major types of spatial learning, exploratory navigation and map reading, were contrasted. By combining a neuroimaging finding that the medial temporal lobe (MTL) is especially important for exploratory navigation and a neurological finding that the MTL is susceptible to age-related atrophy, it was hypothesized that spatial learning through exploratory navigation would exhibit a greater decline in later life than spatial learning through map reading. In an experiment, young and senior participants learned locations of landmarks in virtual environments either by navigating in them in the first-person perspective or by seeing aerial views of the environments. Results showed that senior participants acquired less accurate memories of the layouts of landmarks than young participants when they navigated in the environments, but the two groups did not differ in spatial learning performance when they viewed the environments from the aerial perspective. These results suggest that spatial learning through exploratory navigation is particularly vulnerable to adverse effects of aging, whereas elderly adults may be able to maintain their map reading skills relatively well.

Orientation dependence of spatial memory acquired from auditory experience

The present study investigated whether memory for a room-sized spatial layout learned through auditory localization of sounds exhibits orientation dependence similar to that observed for spatial memory acquired from stationary viewing of the environment. Participants learned spatial layouts by viewing objects or localizing sounds and then performed judgments of relative direction among remembered locations. The results showed that direction judgments following auditory learning were performed most accurately at a particular orientation in the same way as were those following visual learning, indicating that auditorily encoded spatial memory is orientation dependent. In combination with previous findings that spatial memories derived from haptic and proprioceptive experiences are also orientation dependent, the present finding suggests that orientation dependence is a general functional property of human spatial memory independent of learning modality.

Sequential versus simultaneous viewing of an environment : effects of focal attention to individual object locations on visual spatial learning

We investigated memories of room-sized spatial layouts learned by sequentially or simultaneously viewing objects from a stationary position. In three experiments, sequential viewing (one or two objects at a time) yielded subsequent memory performance that was equivalent or superior to simultaneous viewing of all objects, even though sequential viewing lacked direct access to the entire layout. This finding was replicated by replacing sequential viewing with directed viewing in which all objects were presented simultaneously and participants’ attention was externally focused on each object sequentially, indicating that the advantage of sequential viewing over simultaneous viewing may have originated from focal attention to individual object locations. These results suggest that memory representation of object-to-object relations can be constructed efficiently by encoding each object location separately, when those locations are defined within a single spatial reference system. These findings highlight the importance of considering object presentation procedures when studying spatial learning mechanisms.

Visual and proprioceptive representations in spatial memory

It has been shown that spatial information can be acquired from both visual and nonvisual modalities. The present study explored how spatial information from vision and proprioception was represented in memory, investigating orientation dependence of spatial memories acquired through visual and proprioceptive spatial learning. Experiment 1 examined whether visual learning alone and proprioceptive learning alone yielded orientation-dependent spatial memory. Results showed that spatial memories from both types of learning were orientation dependent. Experiment 2 explored how different orientations of the same environment were represented when they were learned visually and proprioceptively. Results showed that both visually and proprioceptively learned orientations were represented in spatial memory, suggesting that participants established two different reference systems based on each type of learning experience and interpreted the environment in terms of these two reference systems. The results provide some initial clues to how different modalities make unique contributions to spatial representations.

An attack-localizing watermarking scheme for natural language documents

We present a text watermarking scheme that embeds a bitstream watermark Wi in a text document P preserving the meaning, context, and flow of the document. The document is viewed as a set of paragraphs, each paragraph being a set of sentences. The sequence of paragraphs and sentences used to embed watermark bits is permuted using a secret key. Then, English language sentence transformations are used to modify sentence lengths, thus embedding watermarking bits in the Least Significant Bits (LSB) of the sentences’ cardinalities. The embedding and extracting algorithms are public, while the secrecy and security of the watermark depends on a secret key K. The probability of False Positives is extremely small, hence avoiding incidental occurrences of our watermark in random text documents. Majority voting provides security against text addition, deletion, and swapping attacks, further reducing the probability of False Positives. The scheme is secure against the general attacks on text watermarks such as reproduction (photocopying, FAX), reformatting, synonym substitution, text addition, text deletion, text swapping, paragraph shuffling and collusion attacks.

Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

Asymptotic minimax robust and misspecified Lorden quickest change detection for dependent stochastic processes

The quick detection of an abrupt unknown change in the conditional distribution of a dependent stochastic process has numerous applications. In this paper, we pose a minimax robust quickest change detection problem for cases where there is uncertainty about the post-change conditional distribution. Our minimax robust formulation is based on the popular Lorden criteria of optimal quickest change detection. Under a condition on the set of possible post-change distributions, we show that the widely known cumulative sum (CUSUM) rule is asymptotically minimax robust under our Lorden minimax robust formulation as a false alarm constraint becomes more strict. We also establish general asymptotic bounds on the detection delay of misspecified CUSUM rules (i.e. CUSUM rules that are designed with post- change distributions that differ from those of the observed sequence). We exploit these bounds to compare the delay performance of asymptotically minimax robust, asymptotically optimal, and other misspecified CUSUM rules. In simulation examples, we illustrate that asymptotically minimax robust CUSUM rules can provide better detection delay performance at greatly reduced computation effort compared to competing generalised likelihood ratio procedures.

On-the-fly web content integrity check boosts users' confidence

Web servers are accessible by anyone who can access the Internet. Although this universal accessibility is attractive for all kinds of Web-based applications, Web servers are exposed to attackers who may want to alter their contents. Alterations range from humorous additions or changes, which are typically easy to spot, to more sinister tampering, such as providing false or damaging information.