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1.
Einstein (Sao Paulo) ; 18: eAO5539, 2020.
Artigo em Inglês, Português | MEDLINE | ID: mdl-33053019

RESUMO

OBJECTIVE: To translate and make cross-cultural adaptation of NECPAL CCOMS-ICO© tool to Portuguese, and to analyze its semantic validity. METHODS: A methodological research about NECPAL CCOMS-ICO© tool cross-cultural adaptation, translated from Spanish into Portuguese and measurement of semantic validity. The cross-cultural adaptation process was conducted according to Beaton recommendations, including translation, translation synthesis, back-translation, and analysis of semantic, idiomatic, conceptual, and cultural equivalence of translated and back-translated tool versions, resulting in a pre-final version, which was submitted to a pre-test (n=35). Contend Validity Index was calculated to analyze semantic validity. RESULTS: Cross-cultural adaptation process allowed us to prepare the final version of this tool, which was named NECPAL-BR. Collected data from pre-testing step enabled the analysis of semantic validity. The Content Validity Index observed at this step was 0.94. CONCLUSION: The semantic validity of the tool in its Portuguese version was confirmed; therefore, it may assist in screening chronic progressive disease patients, aiming to provide early palliative care. It may also be used to develop clinical and team performance indicators, and be employed as a care management tool designed to optimize resources.


Assuntos
Comparação Transcultural , Cuidados Paliativos/normas , Semântica , Inquéritos e Questionários/normas , Humanos , Portugal , Reprodutibilidade dos Testes , Traduções
2.
Nonlinear Dynamics Psychol Life Sci ; 24(4): 389-402, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32960754

RESUMO

This article presents the geometrical-fractal text-tree model of speech and writing, the development of which is part of a project with the long-term goal to answer the question whether Artificial Intelligence and the corresponding human intelligence are principally different or not. Text-tree models consist of word-shrubs 'glued' together by syntax. Word-shrubs are designed by means of two principles, one is the dictionary or semantic principle that we can explain all verbal meanings by the meanings of other words. The other is the initiator-generator procedure, used to develop geometrical fractals. The structure of the word-shrub grows from the root-word when the meaning of the root-word, the generator, is connected as a branch to the root-word which is first initiator. Then all generator words are redefined as new initiators and connected to their meaning, the second generators. But the words or these are redefined as new initiators, each then being connected to its generator-meaning. This is repeated ad infinitum. Each new layer of generators represents a branching level. Consistency of verbal meaning is achieved by fixing the number of branching levels of the word-shrub. Wobbling consistency occurs when the talking or writing person shifts between levels of branching. We develop the M-method, important for most of the results, because it allows differences in verbal meaning to be estimated numerically. An interesting property of the text-tree model is revealed by showing that there must exist a cloud of unexperienced meaning variants of human texts. Most interesting, perhaps, is the demonstration of what we call the lemma of incompleteness which states that humans cannot prove beyond doubt, that they understand correctly what they say and write. This lemma seems to be a distant barrier for the expansion of human understanding and of relevance for understanding human versus artificial intelligence.


Assuntos
Inteligência Artificial , Fractais , Humanos , Semântica
3.
Sensors (Basel) ; 20(18)2020 Sep 12.
Artigo em Inglês | MEDLINE | ID: mdl-32932585

RESUMO

The current COVID-19 pandemic is having a major impact on our daily lives. Social distancing is one of the measures that has been implemented with the aim of slowing the spread of the disease, but it is difficult for blind people to comply with this. In this paper, we present a system that helps blind people to maintain physical distance to other persons using a combination of RGB and depth cameras. We use a real-time semantic segmentation algorithm on the RGB camera to detect where persons are and use the depth camera to assess the distance to them; then, we provide audio feedback through bone-conducting headphones if a person is closer than 1.5 m. Our system warns the user only if persons are nearby but does not react to non-person objects such as walls, trees or doors; thus, it is not intrusive, and it is possible to use it in combination with other assistive devices. We have tested our prototype system on one blind and four blindfolded persons, and found that the system is precise, easy to use, and amounts to low cognitive load.


Assuntos
Inteligência Artificial , Betacoronavirus , Cegueira/reabilitação , Infecções por Coronavirus/prevenção & controle , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Auxiliares Sensoriais , Dispositivos Eletrônicos Vestíveis , Acústica , Adulto , Algoritmos , Inteligência Artificial/estatística & dados numéricos , Cegueira/psicologia , Visão de Cores , Sistemas Computacionais/estatística & dados numéricos , Infecções por Coronavirus/epidemiologia , Desenho de Equipamento , Feminino , Alemanha/epidemiologia , Humanos , Processamento de Imagem Assistida por Computador/estatística & dados numéricos , Masculino , Pneumonia Viral/epidemiologia , Robótica , Semântica , Óculos Inteligentes/estatística & dados numéricos , Distância Social , Pessoas com Deficiência Visual/reabilitação , Dispositivos Eletrônicos Vestíveis/estatística & dados numéricos
4.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 37(4): 641-651, 2020 Aug 25.
Artigo em Chinês | MEDLINE | ID: mdl-32840081

RESUMO

Ultrasonic examination is a common method in thyroid examination, and the results are mainly composed of thyroid ultrasound images and text reports. Implementation of cross modal retrieval method of images and text reports can provide great convenience for doctors and patients, but currently there is no retrieval method to correlate thyroid ultrasound images with text reports. This paper proposes a cross-modal method based on the deep learning and improved cross-modal generative adversarial network: ①the weight sharing constraints between the fully connection layers used to construct the public representation space in the original network are changed to cosine similarity constraints, so that the network can better learn the common representation of different modal data; ②the fully connection layer is added before the cross-modal discriminator to merge the full connection layer of image and text in the original network with weight sharing. Semantic regularization is realized on the basis of inheriting the advantages of the original network weight sharing. The experimental results show that the mean average precision of cross modal retrieval method for thyroid ultrasound image and text report in this paper can reach 0.508, which is significantly higher than the traditional cross-modal method, providing a new method for cross-modal retrieval of thyroid ultrasound image and text report.


Assuntos
Glândula Tireoide , Humanos , Processamento de Imagem Assistida por Computador , Semântica
5.
PLoS One ; 15(8): e0236697, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32785231

RESUMO

Two cross-modal priming experiments were conducted to investigate morphological processing in Chinese spoken word recognition during sentence comprehension. Participants heard sentences that contained opaque prime words and performed lexical decisions on visual targets that were related to second morpheme meanings of opaque words or whole-word meanings. The targets were presented at the auditory onset of the second morphemes or the subsequent syllables after the opaque primes to examine the time course of effects. In a neutral sentence context (Experiment 1), opaque word morpheme meanings produced morphological priming on target word recognition, which preceded lexical priming. When context biased toward whole opaque words (Experiment 2), morphological priming disappeared, while the effect of lexical meanings remained significant and emerged earlier than the effect of lexical meanings in the neutral context. These findings suggest that morphemes play a role in Chinese spoken word recognition, but their effects depend on the prior context during sentence comprehension.


Assuntos
Compreensão/fisiologia , Idioma , Fonética , Semântica , Adulto , China , Feminino , Humanos , Masculino , Priming de Repetição/fisiologia , Vocabulário , Adulto Jovem
6.
BMC Bioinformatics ; 21(1): 339, 2020 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-32736513

RESUMO

BACKGROUND: It has been widely accepted that long non-coding RNAs (lncRNAs) play important roles in the development and progression of human diseases. Many association prediction models have been proposed for predicting lncRNA functions and identifying potential lncRNA-disease associations. Nevertheless, among them, little effort has been attempted to measure lncRNA functional similarity, which is an essential part of association prediction models. RESULTS: In this study, we presented an lncRNA functional similarity calculation model, IDSSIM for short, based on an improved disease semantic similarity method, highlight of which is the introduction of information content contribution factor into the semantic value calculation to take into account both the hierarchical structures of disease directed acyclic graphs and the disease specificities. IDSSIM and three state-of-the-art models, i.e., LNCSIM1, LNCSIM2, and ILNCSIM, were evaluated by applying their disease semantic similarity matrices and the lncRNA functional similarity matrices, as well as corresponding matrices of human lncRNA-disease associations coming from either lncRNADisease database or MNDR database, into an association prediction method WKNKN for lncRNA-disease association prediction. In addition, case studies of breast cancer and adenocarcinoma were also performed to validate the effectiveness of IDSSIM. CONCLUSIONS: Results demonstrated that in terms of ROC curves and AUC values, IDSSIM is superior to compared models, and can improve accuracy of disease semantic similarity effectively, leading to increase the association prediction ability of the IDSSIM-WKNKN model; in terms of case studies, most of potential disease-associated lncRNAs predicted by IDSSIM can be confirmed by databases and literatures, implying that IDSSIM can serve as a promising tool for predicting lncRNA functions, identifying potential lncRNA-disease associations, and pre-screening candidate lncRNAs to perform biological experiments. The IDSSIM code, all experimental data and prediction results are available online at https://github.com/CDMB-lab/IDSSIM .


Assuntos
Algoritmos , Biologia Computacional/métodos , Doença/genética , Modelos Genéticos , RNA Longo não Codificante/genética , Semântica , Adenocarcinoma/genética , Área Sob a Curva , Neoplasias da Mama/genética , Bases de Dados Genéticas , Feminino , Humanos , Curva ROC
7.
PLoS One ; 15(8): e0237767, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32853283

RESUMO

Multiword Expressions (MWEs) are idiosyncratic combinations of words which pose important challenges to Natural Language Processing. Some kinds of MWEs, such as verbal ones, are particularly hard to identify in corpora, due to their high degree of morphosyntactic flexibility. This paper describes a linguistically motivated method to gather detailed information about verb+noun MWEs (VNMWEs) from corpora. Although the main focus of this study is Spanish, the method is easily adaptable to other languages. Monolingual and parallel corpora are used as input, and data about the morphosyntactic variability of VNMWEs is extracted. This information is then tested in an identification task, obtaining an F score of 0.52, which is considerably higher than related work.


Assuntos
Processamento de Linguagem Natural , Semântica , Vocabulário
8.
PLoS One ; 15(8): e0235810, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32810171

RESUMO

Anomia is common in Primary Progressive Aphasia (PPA), and there is considerable evidence that semantic problems (as opposed to impaired access to output word phonology) exist in many PPA individuals irrespective of their strict subtype, including a loss of representations from semantic memory, which is typical for people with the semantic variant of PPA. In this manuscript we present a straightforward novel clinical algorithm that quantifies this degree of semantic storage impairment. We sought to produce an algorithm by employing tasks that would measure key elements of semantic storage loss: a) whether an unrecalled name could be retrieved with cues; b) if performance for items was consistent across tasks; and c) the degree to which a participant's performance was related to general severity of cognitive impairment rather than semantic loss. More specifically, these tasks were given to 28 individuals with PPA (12 participants had a clinical diagnosis of atypical Alzheimer's Disease with the logopenic variant of PPA; the remaining 16 participants received a clinical diagnosis of Frontotemporal dementia (11 were classified as the non-fluent variant of PPA and five were the semantic variant of PPA). Scores from these tasks produced a single omnibus semantic memory storage loss score (SSL score) for each person that ranged from 0.0 to 1.0, with scores closer to 0 more indicative of semantic storage loss. Indeed, supporting the hypothesis that our scores measure the degree of semantic storage loss, we found participants with the semantic variant of PPA had the lowest scores, and SSL scores could predict the degree of hypometabolism in the anterior temporal lobe; even when only people with the logopenic variant of PPA were examined. Thus, these scores show promise quantitating the degree of a person's semantic representation loss.


Assuntos
Afasia Primária Progressiva/fisiopatologia , Doenças Neurodegenerativas/fisiopatologia , Semântica , Lobo Temporal/fisiopatologia , Idoso , Idoso de 80 Anos ou mais , Doença de Alzheimer/complicações , Doença de Alzheimer/metabolismo , Doença de Alzheimer/fisiopatologia , Afasia Primária Progressiva/etiologia , Afasia Primária Progressiva/metabolismo , Feminino , Demência Frontotemporal/complicações , Demência Frontotemporal/metabolismo , Demência Frontotemporal/fisiopatologia , Humanos , Masculino , Doenças Neurodegenerativas/complicações , Doenças Neurodegenerativas/metabolismo , Testes Neuropsicológicos , Tomografia por Emissão de Pósitrons , Lobo Temporal/metabolismo
9.
Stud Health Technol Inform ; 272: 461-464, 2020 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-32604702

RESUMO

The heterogeneous localized concepts of various hospitals reduce interoperability among localized data models of Hospital Information Systems (HIS) and the knowledge bases of clinical decision support systems (CDSS). The leading solution to overcome the interoperability barrier is the reconciliation of standard medical terminologies with localized data models. In this paper, we extend the semantic reconciliation model (SRM) to provide mappings among diverse concepts of localized domain clinical models (DCM) and concepts of standard medical terminologies such as Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). In the extended SRM, we insert the explicit semantics only into the word vector of the localized DCM concepts instead of the implicit semantics, which enhances the system's accuracy with a lower computational cost. The extended SRM performed well on the datasets of localized DCM and SNOMED CT with a precision of 0.95, a recall of 0.92, and an F-measure of 0.93.


Assuntos
Sistemas de Apoio a Decisões Clínicas , Semântica , Bases de Conhecimento , Systematized Nomenclature of Medicine
10.
Stud Health Technol Inform ; 272: 159-162, 2020 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-32604625

RESUMO

The successful introduction of ICTs into medical practice is a key factor in improving the performance of any health system for both patients and healthcare professionals. In Burkina Faso, many hospital information systems (HIS) have been developed and are already widely used in large health centers with proven efficiency. To improve the quality of patient care, these hospital information systems should exchange information. Interoperability is one of the privileged ways to improve the integration of different systems because nowadays a HIS is no longer just a single monolithic software system, which is run on a single machine. This paper presents a semantic interoperability architecture, which is based on a mediation approach. The mediator implements local domain ontologies for each HIS, a knowledge base, and a referential ontology which is used as a semantic repository and web services.


Assuntos
Sistemas de Informação Hospitalar , Burkina Faso , Humanos , Bases de Conhecimento , Semântica , Software
11.
Behav Brain Sci ; 43: e152, 2020 06 19.
Artigo em Inglês | MEDLINE | ID: mdl-32645800

RESUMO

Although many simulations draw upon only one level of abstraction, the process for generating rich simulations requires a dynamic interplay between abstract and concrete knowledge. A complete model of simulation must account for a mind and brain that can bridge the perceptual with the conceptual, the episodic with the semantic, and the concrete with the abstract.


Assuntos
Encéfalo , Semântica , Conhecimento
12.
PLoS One ; 15(7): e0234880, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32645050

RESUMO

This paper introduces a measure of the proximity in ideas using unsupervised machine learning. Knowledge transfers are considered a key driving force of innovation and regional economic growth. I explore knowledge relationships by deriving vector space representations of a patent's abstract text using Document Vectors (Doc2Vec), and using cosine similarity to measure their proximity in ideas space. I illustrate the potential uses of this method with an application to geographic localization in knowledge spillovers. For patents in the same technology field, their normalized text similarity is 0.02-0.05 S.D.s higher if they are located within the same city, compared to patents from other cities. This effect is much smaller than when knowledge transfers are measured using normalized patent citations: local patents receive about 0.23-0.30 S.D.s more local citations than compared to non-local control patents. These findings suggest that the effect of geography on knowledge transfers may be much smaller than the previous literature using citations suggests.


Assuntos
Disseminação de Informação/história , Invenções/tendências , Patentes como Assunto/história , História do Século XX , História do Século XXI , Humanos , Conhecimento , Idioma , Aprendizado de Máquina , Modelos Estatísticos , Semântica , Aprendizado de Máquina não Supervisionado
13.
PLoS One ; 15(7): e0236388, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32730342

RESUMO

PURPOSE: In this study we investigated a set of 100 sentence contexts and their cloze probabilities to develop a database of linguistic stimuli for Brazilian Portuguese children and adolescents. The study also examined age-related changes on cloze probabilities, and specified the predictor effects of age and cloze probabilities on idiosyncratic responses and errors (semantic, syntactic, and other errors). Finally, the study also aimed to shed light on cultural effects on word generation by comparing Brazilian and Portuguese sentence databases. METHOD: 361 typically developing monolingual Brazilian speakers, with ages ranging from 7 to 18 years, participated in the study. The cloze task was composed by 100 sentence contexts, grounded on the European Portuguese database. Responses were classified as valid (correct) or invalid (semantic, syntactic, and other-type errors). Statistical analyses were based on mixed-effects logistic models. RESULTS: Sixty-three sentences met criteria for high cloze probabilities, 30 for medium cloze, and 7 for low cloze. Age was a significant predictor of idiosyncratic responses, semantic and syntactic errors: older participants were less likely to produce idiosyncratic responses, as well as semantic and syntactic errors. Cloze probability values were concordant in the Brazilian and Portuguese databases for 31 out of 49 (83.7%) high-cloze sentences and for 7 low-cloze sentences. CONCLUSION: In this study we have provided a database with cloze probability values for a set of 100 sentence-final word contexts for Brazilian Portuguese children and adolescents. Results showed that both age and sentence contextual level predicted sentence final word completion. Older participants were more likely to choose more consistently the same final word, with the contextual level of a given sentence also contributing to the final word selection. Age should be controlled for in future studies probing semantic processing with this set of sentences.


Assuntos
Probabilidade , Semântica , Adolescente , Brasil , Criança , Feminino , Humanos , Masculino
14.
PLoS One ; 15(7): e0235670, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32645039

RESUMO

BACKGROUND: Biomedical ontologies have been growing quickly and proven to be useful in many biomedical applications. Important applications of those data include estimating the functional similarity between ontology terms and between annotated biomedical entities, analyzing enrichment for a set of biomedical entities. Many semantic similarity calculation and enrichment analysis methods have been proposed for such applications. Also, a number of tools implementing the methods have been developed on different platforms. However, these tools have implemented a small number of the semantic similarity calculation and enrichment analysis methods for a certain type of biomedical ontology. Note that the methods can be applied to all types of biomedical ontologies. More importantly, each method can be dominant in different applications; thus, users have more choice with more number of methods implemented in tools. Also, more functions would facilitate their task with ontology. RESULTS: In this study, we developed a Cytoscape app, named UFO, which unifies most of the semantic similarity measures for between-term and between-entity similarity calculation for all types of biomedical ontologies in OBO format. Based on the similarity calculation, UFO can calculate the similarity between two sets of entities and weigh imported entity networks as well as generate functional similarity networks. Besides, it can perform enrichment analysis of a set of entities by different methods. Moreover, UFO can visualize structural relationships between ontology terms, annotating relationships between entities and terms, and functional similarity between entities. Finally, we demonstrated the ability of UFO through some case studies on finding the best semantic similarity measures for assessing the similarity between human disease phenotypes, constructing biomedical entity functional similarity networks for predicting disease-associated biomarkers, and performing enrichment analysis on a set of similar phenotypes. CONCLUSIONS: Taken together, UFO is expected to be a tool where biomedical ontologies can be exploited for various biomedical applications. AVAILABILITY: UFO is distributed as a Cytoscape app, and can be downloaded freely at Cytoscape App (http://apps.cytoscape.org/apps/ufo) for non-commercial use.


Assuntos
Ontologias Biológicas , Software , Biomarcadores , Testes Diagnósticos de Rotina , Humanos , Semântica , Vocabulário Controlado
15.
Neuropsychiatr ; 34(3): 140-147, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32608011

RESUMO

BACKGROUND: Due to the increase of dementia diagnoses and individuals interested in monitoring their cognitive status, practical new neuropsychological tests are needed. Tablet-based tests offer a good alternative to traditional paper-pencil tests, as they can be completed remotely and independently. This study assessed two semantic memory tests (verbal and visual memory), in the scope of the creation of a new tablet-based battery-the International Neurocognitive Profil (INCP)-on the influences of demographic variables. METHODS: In all, 46 cognitively healthy participants who recruited at the memory clinic of the Medical University of Vienna were included in this study. They were asked to complete two tests of semantic memory and implicit learning: Capital Knowledge (CK) using verbal input and Flag Knowledge (FK) using visual input. Performance on the two tests was analysed according to influences of gender and age using two analyses of variance. Post hoc comparisons between age and gender groups were performed. In addition, correlational analyses were computed to assess strengths of association with age, gender and education. RESULTS: FK- and CK-based measures were found to be influenced by demographic variables with semantic memory measures being significantly influenced by gender and education while incidental memory measures were influenced by age. Performances differed between FK and CK showing that the mode of testing (visual, verbal) affected participant's performance. CONCLUSION: These findings are important for the creation of normative samples for both CK and FK. Furthermore, this study underlines the importance of using different testing modes when assessing individuals' semantic memory.


Assuntos
Transtornos Cognitivos , Memória , Semântica , Cognição , Transtornos Cognitivos/diagnóstico , Humanos , Testes Neuropsicológicos , Projetos Piloto
16.
PLoS One ; 15(7): e0234894, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32667959

RESUMO

We present a multi-agent computational approach to partitioning semantic spaces using reinforcement-learning (RL). Two agents communicate using a finite linguistic vocabulary in order to convey a concept. This is tested in the color domain, and a natural reinforcement learning mechanism is shown to converge to a scheme that achieves a near-optimal trade-off of simplicity versus communication efficiency. Results are presented both on the communication efficiency as well as on analyses of the resulting partitions of the color space. The effect of varying environmental factors such as noise is also studied. These results suggest that RL offers a powerful and flexible computational framework that can contribute to the development of communication schemes for color names that are near-optimal in an information-theoretic sense and may shape color-naming systems across languages. Our approach is not specific to color and can be used to explore cross-language variation in other semantic domains.


Assuntos
Comunicação , Reforço Psicológico , Semântica , Cor , Percepção de Cores , Humanos , Idioma , Aprendizagem , Linguística/estatística & dados numéricos , Modelos Teóricos , Nomes , Vocabulário
17.
PLoS One ; 15(7): e0236347, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32702022

RESUMO

Measuring the semantic similarity between words is important for natural language processing tasks. The traditional models of semantic similarity perform well in most cases, but when dealing with words that involve geographical context, spatial semantics of implied spatial information are rarely preserved. Geographic information retrieval (GIR) methods have focused on this issue; however, they sometimes fail to solve the problem because the spatial and textual similarities of words are considered and calculated separately. In this paper, from the perspective of spatial context, we consider the two parts as a whole-spatial context semantics, and we propose a method that measures spatial semantic similarity using a sliding geospatial context window for geo-tagged words. The proposed method was first validated with a set of simulated data and then applied to a real-world dataset from Flickr. As a result, a spatial semantic similarity model at different scales is presented. We believe this model is a necessary supplement for traditional textual-language semantic analyses of words obtained by word-embedding technologies. This study has the potential to improve the quality of recommendation systems by considering relevant spatial context semantics, and benefits linguistic semantic research by emphasising the spatial cognition among words.


Assuntos
Idioma , Linguística/tendências , Processamento de Linguagem Natural , Semântica , Algoritmos , Compreensão , Humanos , Armazenamento e Recuperação da Informação , PubMed
18.
Stud Health Technol Inform ; 270: 1327-1328, 2020 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-32570642

RESUMO

Extracting patient phenotypes from routinely collected health data (such as Electronic Health Records) requires translating clinically-sound phenotype definitions into queries/computations executable on the underlying data sources by clinical researchers. This requires significant knowledge and skills to deal with heterogeneous and often imperfect data. Translations are time-consuming, error-prone and, most importantly, hard to share and reproduce across different settings. This paper proposes a knowledge driven framework that (1) decouples the specification of phenotype semantics from underlying data sources; (2) can automatically populate and conduct phenotype computations on heterogeneous data spaces. We report preliminary results of deploying this framework on five Scottish health datasets.


Assuntos
Registros Eletrônicos de Saúde , Armazenamento e Recuperação da Informação , Semântica
19.
PLoS One ; 15(6): e0234486, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32525909

RESUMO

This article employs computer-assisted methods to analyse references to Aboriginal and Torres Strait Islander people(s) and issues in a newspaper corpus about diabetes. The objectives are to identify both the frequency and quality of social representation. The dataset consisted of 694 items from 12 Australian newspapers in a five-year period (2013-2017). The quantitative analysis focused on frequency (raw/normalised) and range (number/percentage of texts). The qualitative analysis focused on the identification of semantic prosody (co-occurrence with negative/positive words and phrases) and on selective social actor analysis. The qualitative analysis also compared choices made by the press to language practices recommended in relevant reporting guidelines. Key results include that references to Aboriginal and Torres Strait Islander people(s) or matters appear to be extremely rare. In addition, newspapers' language choices only partially align with guidelines. References that do occur can be classified into four categories: a) references to [groups of] people and other references to identity; b) names of services, institutions, professions, roles etc; c) non-human nouns related to health; d) non-human nouns related to culture. Qualitative analysis of the word COMMUNITY suggests that newspapers for the most part do recognise the existence of different communities at a national level. However, analysis of all references to [groups of] people shows that the vast majority occur in contexts to do with negativity, therefore having a negative semantic prosody. More specifically, there is a strong association with mentions of a higher risk, likelihood, or incidence of having or developing diabetes (or complications/effects). In sum, Aboriginal and Torres Strait Islander people(s) and issues lack in visibility in Australian diabetes coverage, and are associated with deficit framing, which can be disempowering. To change the discourse would require both an increased visibility as well as changing the deficit lens.


Assuntos
Análise de Dados , Diabetes Mellitus/epidemiologia , Jornais como Assunto/ética , Grupo com Ancestrais Oceânicos/estatística & dados numéricos , Semântica , Austrália/epidemiologia , Conjuntos de Dados como Assunto , Diabetes Mellitus/prevenção & controle , Necessidades e Demandas de Serviços de Saúde , Serviços de Saúde do Indígena/organização & administração , Serviços de Saúde do Indígena/estatística & dados numéricos , Humanos , Incidência , Jornais como Assunto/estatística & dados numéricos , Pesquisa Qualitativa
20.
Stud Health Technol Inform ; 270: 362-366, 2020 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-32570407

RESUMO

Parallel sentences provide semantically similar information which can vary on a given dimension, such as language or register. Parallel sentences with register variation (like expert and non-expert documents) can be exploited for the automatic text simplification. The aim of automatic text simplification is to better access and understand a given information. In the biomedical field, simplification may permit patients to understand medical and health texts. Yet, there is currently no such available resources. We propose to exploit comparable corpora which are distinguished by their registers (specialized and simplified versions) to detect and align parallel sentences. These corpora are in French and are related to the biomedical area. We treat this task as binary classification (alignment/non-alignment). Our results show that the method we present here can be used to automatically generate a corpus of parallel sentences from our comparable corpus.


Assuntos
Idioma , Processamento de Linguagem Natural , Compreensão , Semântica , Unified Medical Language System
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