Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction

Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.

Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.

Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.

Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.

Beyond the Acronyms: Sport Diplomacy and the Classification of the International Olympic Committee

Diplomacy often finds itself reduced to actions centred on states. However, after the Cold War, international relations and diplomacy have expanded with different actors growing into significant roles, particularly in the increase of diplomatic relations in the context of sport. The classification and significance of other actors remains under-researched in relation to sport, with literature focusing more on the growth of new and varying practices of diplomacy. This analysis contends that there is a need to interrogate fundamental components of modern diplomacy—with the actor being the focus—more specifically the classification of sports organisations in diplomacy. It is relevant as a more accurate understanding of sports organisations will contribute to how diplomatic studies can analyse and evaluate modern diplomacy within the context of sport. The International Olympic Committee is the actor used to illustrate how problematic classifications currently in the academic literature translate into weak and reduced analysis and evaluation of its role and significance in diplomacy. As counterpoint, this analysis proposes an analytical framework of socio-legal theory that harnesses legal regulation as a benchmark to classify an actor’s capacity within a society. In consequence, the IOC is as an active and significant contributor to the ever expanding and complex diplomatic environment and wider society.

Second-order cyclostationarity-based detection and classification of LTE SC-FDMA signals for cognitive radio

Cognitive radio (CR) was developed for utilizing the spectrum bands efficiently. Spectrum sensing and awareness represent main tasks of a CR, providing the possibility of exploiting the unused bands. In this thesis, we investigate the detection and classification of Long Term Evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) signals, which are used in uplink LTE, with applications to cognitive radio. We explore the second-order cyclostationarity of the LTE SC-FDMA signals, and apply results obtained for the cyclic autocorrelation function to signal detection and classification (in other words, to spectrum sensing and awareness). The proposed detection and classification algorithms provide a very good performance under various channel conditions, with a short observation time and at low signal-to-noise ratios, with reduced complexity. The validity of the proposed algorithms is verified using signals generated and acquired by laboratory instrumentation, and the experimental results show a good match with computer simulation results.

Stroke severity, early recovery and outcome are each related with clinical classification of stroke: data from the 'Tinzaparin in Acute Ischaemic Stroke Trial (TAIST)

Introduction: Baseline severity and clinical stroke syndrome (Oxford Community Stroke Project, OCSP) classification are predictors of outcome in stroke. We used data from the ‘Tinzaparin in Acute Ischaemic Stroke Trial’ (TAIST) to assess the relationship between stroke severity, early recovery, outcome and OCSP syndrome. Methods: TAIST was a randomised controlled trial assessing the safety and efficacy of tinzaparin versus aspirin in 1,484 patients with acute ischaemic stroke. Severity was measured as the Scandinavian Neurological Stroke Scale (SNSS) at baseline and days 4, 7 and 10, and baseline OCSP clinical classification recorded: total anterior circulation infarct (TACI), partial anterior circulation infarct (PACI), lacunar infarct (LACI) and posterior circulation infarction (POCI). Recovery was calculated as change in SNSS from baseline at day 4 and 10. The relationship between stroke syndrome and SNSS at days 4 and 10, and outcome (modified Rankin scale at 90 days) were assessed. Results: Stroke severity was significantly different between TACI (most severe) and LACI (mildest) at all four time points (p<0.001), with no difference between PACI and POCI. The largest change in SNSS score occurred between baseline and day 4; improvement was least in TACI (median 2 units), compared to other groups (median 3 units) (p<0.001). If SNSS did not improve by day 4, then early recovery and late functional outcome tended to be limited irrespective of clinical syndrome (SNSS, baseline: 31, day 10: 32; mRS, day 90: 4); patients who recovered early tended to continue to improve and had better functional outcome irrespective of syndrome (SNSS, baseline: 35, day 10: 50; mRS, day 90: 2). Conclusions: Although functional outcome is related to baseline clinical syndrome (best with LACI, worst with TACI), patients who improve early have a more favourable functional outcome, irrespective of their OCSP syndrome. Hence, patients with a TACI syndrome may still achieve a reasonable outcome if early recovery occurs.

A Phylogenetic Classification of the Video-Game Industry’s Business Model Ecosystem

Part 8: Business Strategies Alignment

Incidence and classification of bifid mandibular canals using cone beam computed tomography

Aim: To determine the prevalence and classification of bifid mandibular canals using cone beam computed tomography (CBCT). Methods: The sample comprised 300 CBCT scans obtained from the Radiology and Imaging Department database at São Leopoldo Mandic Dental School, Campinas, SP, Brazil. All images were performed on Classic I-Cat® CBCT scanner, with standardized voxel at 0.25 mm and 13 cm FOV (field of view). From an axial slice (0.25 mm) a guiding plane was drawn along the alveolar ridge in order to obtain a cross-section. Results: Among 300 patients, 188 (62.7%) were female and 112 (37.3%) were male, aged between 13 to 87 years. Changes in the mandibular canal were observed in 90 patients, 30.0% of the sample, 51 women (56.7%) and 39 men (43.3%). Regarding affected sides, 32.2% were on the right and 24.5% on the left, with 43.3% bilateral cases. Conclusions: According to the results obtained in this study, a prevalence of 30% of bifid mandibular canals was found, with the most prevalent types classified as B (mesial direction) and bilateral.

Classification of plant communities, structure and diversity of forests in Acre, Brazil.

2016

An updated evolutionary classification of CRISPR–Cas systems

The evolution of CRISPR–cas loci, which encode adaptive immune systems in archaea and bacteria, involves rapid changes, in particular numerous rearrangements of the locus architecture and horizontal transfer of complete loci or individual modules. These dynamics complicate straightforward phylogenetic classification, but here we present an approach combining the analysis of signature protein families and features of the architecture of cas loci that unambiguously partitions most CRISPR–cas loci into distinct classes, types and subtypes. The new classification retains the overall structure of the previous version but is expanded to now encompass two classes, five types and 16 subtypes. The relative stability of the classification suggests that the most prevalent variants of CRISPR–Cas systems are already known. However, the existence of rare, currently unclassifiable variants implies that additional types and subtypes remain to be characterized.

Comparing children's self-report instruments for health-related quality of life using the International Classification of Functioning, Disability and Health for Children and Youth (ICF-CY)

Children with chronic conditions often experience a long treatment which can be complex and negatively impacts the child's well-being. In planning treatment and interventions for children with chronic conditions, it is important to measure health-related quality of life (HrQoL). HrQoL instruments are considered to be a patient-reported outcome measure (PROM) and should be used in routine practice. Purpose: The aim of this study was to compare the content dimensions of HrQoL instruments for children's self-reports using the framework of ICF-CY. Method: The sample consist of six instruments for health-related quality of life for children 5 to 18 years of age, which was used in the Swedish national quality registries for children and adolescents with chronic conditions. The following instruments were included: CHQ-CF, DCGM-37, EQ-5D-Y, KIDSCREEN-52, Kid-KINDL and PedsQL 4.0. The framework of the ICF-CY was used as the basis for the comparison. Results: There were 290 meaningful concepts identified and linked to 88 categories in the classification ICF-CY with 29 categories of the component body functions, 48 categories of the component activities and participation and 11 categories of the component environmental factors. No concept were linked to the component body structures. The comparison revealed that the items in the HrQoL instruments corresponded primarily with the domains of activities and less with environmental factors. Conclusions: In conclusion, the results confirm that ICF-CY provide a good framework for content comparisons that evaluate similarities and differences to ICF-CY categories. The results of this study revealed the need for greater consensus of content across different HrQoL instruments. To obtain a detailed description of children's HrQoL, DCGM-37 and KIDSCREEN-52 may be appropriate instruments to use that can increase the understanding of young patients' needs.

Genesis and classification of soils from subtropical mountain regions of Southern Brazil.

Soils formed in high mountainous regions in southern Brazil are characterized by great accumulation of organic matter (OM) in the surface horizons and variation in the degree of development. We hypothesized that soil properties and genesis are influenced by the interaction of parent materials and climate factors, which differ depending on the location along the altitudinal gradient. The goal of this study was to characterize and classify the soil, evaluate soil distribution, and determine the interactive effects of soil-forming factors in the subtropical mountain regions in Santa Catarina state. Soil samples were collected in areas known for wine production, for a total of 38 modal profiles. Based on morphological, physical, and chemical properties, soils were evaluated for pedogenesis and classified according to the Brazilian System of Soil Classification, with equivalent classes in the World Reference Basis (WRB). The results indicated that pedogenesis was strongly influenced by the parent material, weather, and relief. In the areas where basic effusive rocks (basalt) were observed, there was formation of extensive areas of clayey soils with reddish color and higher iron oxide contents. There was a predominance of Nitossolos Vermelhos and Háplicos (Nitisols), Latossolos Vermelhos (Ferralsols), and Cambissolos Háplicos (Cambisols), highlighting the pedogenetic processes of eluviation, illuviation of clay, and latosolization in conditions of year-long, large-volume, well-distributed rainfall and stability of land forms. In areas with acid effusive rocks (rhyodacites), medial or clayey soils were observed with lower iron oxide content, invariably acidic, and with low base content. For these soils, relief promoted substantial removal of material, resulting in intense rejuvenation, with a predominance of Cambissolos Háplicos (Cambisols) and lesser occurrence of Nitossolos Brunos (Nitisols) and Neossolos Litólicos (Leptosols). Soils formed from sedimentary rocks also tended to be more acidic, but with higher sand content, and the soils identified were Cambissolos Háplicos and Húmicos (Cambisols). Cluster analysis separated the soil profiles into three groups: the first and largest was formed by profiles originating from sedimentary rocks and rhyodacites; the second, smaller group was formed by four profiles in the Água Doce region (acidic rocks); and the third was formed by profiles derived from basalt. Discriminant analysis was effective in grouping soil classes. Thus, the study highlighted the importance of geology in the formation of soils in this landscape associated with climate and relief.

Automatic classification of stellar orbits in axisymmetric potentials

Within the classification of orbits in axisymmetric stellar systems, we present a new algorithm able to automatically classify the orbits according to their nature. The algorithm involves the application of the correlation integral method to the surface of section of the orbit; fitting the cumulative distribution function built with the consequents in the surface of section of the orbit, we can obtain the value of its logarithmic slope m which is directly related to the orbit’s nature: for slopes m ≈ 1 we expect the orbit to be regular, for slopes m ≈ 2 we expect it to be chaotic. With this method we have a fast and reliable way to classify orbits and, furthermore, we provide an analytical expression of the probability that an orbit is regular or chaotic given the logarithmic slope m of its correlation integral. Although this method works statistically well, the underlying algorithm can fail in some cases, misclassifying individual orbits under some peculiar circumstances. The performance of the algorithm benefits from a rich sampling of the traces of the SoS, which can be obtained with long numerical integration of orbits. Finally we note that the algorithm does not differentiate between the subtypes of regular orbits: resonantly trapped and untrapped orbits. Such distinction would be a useful feature, which we leave for future work. Since the result of the analysis is a probability linked to a Gaussian distribution, for the very definition of distribution, some orbits even if they have a certain nature are classified as belonging to the opposite class and create the probabilistic tails of the distribution. So while the method produces fair statistical results, it lacks in absolute classification precision.

O papel da equivalência de contato na Cr-classificação de germes de aplicações Cr-estáveis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)