Displaying publications 1 - 20 of 444 in total

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  1. Chai JH, Lo CH, Mayor J
    J Speech Lang Hear Res, 2020 10 16;63(10):3488-3500.
    PMID: 32897770 DOI: 10.1044/2020_JSLHR-20-00361
    Purpose This study introduces a framework to produce very short versions of the MacArthur-Bates Communicative Development Inventories (CDIs) by combining the Bayesian-inspired approach introduced by Mayor and Mani (2019) with an item response theory-based computerized adaptive testing that adapts to the ability of each child, in line with Makransky et al. (2016). Method We evaluated the performance of our approach-dynamically selecting maximally informative words from the CDI and combining parental response with prior vocabulary data-by conducting real-data simulations using four CDI versions having varying sample sizes on Wordbank-the online repository of digitalized CDIs: American English (a very large data set), Danish (a large data set), Beijing Mandarin (a medium-sized data set), and Italian (a small data set). Results Real-data simulations revealed that correlations exceeding .95 with full CDI administrations were reached with as few as 15 test items, with high levels of reliability, even when languages (e.g., Italian) possessed few digitalized administrations on Wordbank. Conclusions The current approach establishes a generic framework that produces very short (less than 20 items) adaptive early vocabulary assessments-hence considerably reducing their administration time. This approach appears to be robust even when CDIs have smaller samples in online repositories, for example, with around 50 samples per month-age.
    Matched MeSH terms: Child Language*; Language Development
  2. Sahaimi MF, Mat Pa MN, Taib F
    Malays J Med Sci, 2020 Jul;27(4):97-107.
    PMID: 32863749 MyJurnal DOI: 10.21315/mjms2020.27.4.9
    Background: Childhood maltreatment is a global problem, for which the International Society for the Prevention of Child Abuse and Neglect (ISPCAN) has developed the Child Abuse Screening Tool-Child, Home Version (ICAST-CH) to obtain data concerning childhood maltreatment. The study aimed to translate the English version of the ICAST-CH into the Malay language and to assess its reliability and validity.

    Methods: The original English version of the ICAST-CH was first translated into the Malay language. Its content and face validity were tested among five independent individuals. A cross-sectional study using the Malay version (ICAST-CH-M) was then conducted with 255 students in a secondary school in Kota Bharu, Kelantan, Malaysia. The data collected was used to examine the instrument's internal consistency and construct validity. The best ICAST-CH-M model was achieved after varimax rotation application.

    Results: The analysis showed that the Malay version of the ICAST-CH had satisfactory internal consistency, with Cronbach's alpha ranging from 0.59-0.77. The exploratory factor analysis confirmed the validity of the underlying constructs into five domains in the Malay version, but they had to be re-classified as 'physical and psychological abuse', 'neglect', 'sexual abuse', 'exposure to domestic violence' and 'exposure to community violence'.

    Conclusion: This study demonstrated that the ICAST-CH-M is satisfactorily reliable and valid for measuring child maltreatment in Malaysia.

    Matched MeSH terms: Language
  3. Kapitaniak T, Mohammadi SA, Mekhilef S, Alsaadi FE, Hayat T, Pham VT
    Entropy (Basel), 2018 Sep 05;20(9).
    PMID: 33265759 DOI: 10.3390/e20090670
    In this paper, we introduce a new, three-dimensional chaotic system with one stable equilibrium. This system is a multistable dynamic system in which the strange attractor is hidden. We investigate its dynamic properties through equilibrium analysis, a bifurcation diagram and Lyapunov exponents. Such multistable systems are important in engineering. We perform an entropy analysis, parameter estimation and circuit design using this new system to show its feasibility and ability to be used in engineering applications.
    Matched MeSH terms: Language
  4. Ibrahim IA, Ting HN, Moghavvemi M
    J Int Adv Otol, 2019 Apr;15(1):87-93.
    PMID: 30924771 DOI: 10.5152/iao.2019.4553
    OBJECTIVES: This study uses a new approach for classifying the human ethnicity according to the auditory brain responses (electroencephalography [EEG] signals) with a high level of accuracy. Moreover, the study presents three different algorithms used to classify the human ethnicity using auditory brain responses. The algorithms were tested on Malays and Chinese as a case study.

    MATERIALS AND METHODS: The EEG signal was used as a brain response signal, which was evoked by two auditory stimuli (Tones and Consonant Vowels stimulus). The study was carried out on Malaysians (Malay and Chinese) with normal hearing and with hearing loss. A ranking process for the subjects' EEG data and the nonlinear features was used to obtain the maximum classification accuracy.

    RESULTS: The study formulated the classification of Normal Hearing Ethnicity Index and Sensorineural Hearing Loss Ethnicity Index. These indices classified the human ethnicity according to brain auditory responses by using numerical values of response signal features. Three classification algorithms were used to verify the human ethnicity. Support Vector Machine (SVM) classified the human ethnicity with an accuracy of 90% in the cases of normal hearing and sensorineural hearing loss (SNHL); the SVM classified with an accuracy of 84%.

    CONCLUSION: The classification indices categorized or separated the human ethnicity in both hearing cases of normal hearing and SNHL with high accuracy. The SVM classifier provided a good accuracy in the classification of the auditory brain responses. The proposed indices might constitute valuable tools for the classification of the brain responses according to the human ethnicity.

    Matched MeSH terms: Language
  5. Rahman MM, Usman OL, Muniyandi RC, Sahran S, Mohamed S, Razak RA
    Brain Sci, 2020 Dec 07;10(12).
    PMID: 33297436 DOI: 10.3390/brainsci10120949
    Autism Spectrum Disorder (ASD), according to DSM-5 in the American Psychiatric Association, is a neurodevelopmental disorder that includes deficits of social communication and social interaction with the presence of restricted and repetitive behaviors. Children with ASD have difficulties in joint attention and social reciprocity, using non-verbal and verbal behavior for communication. Due to these deficits, children with autism are often socially isolated. Researchers have emphasized the importance of early identification and early intervention to improve the level of functioning in language, communication, and well-being of children with autism. However, due to limited local assessment tools to diagnose these children, limited speech-language therapy services in rural areas, etc., these children do not get the rehabilitation they need until they get into compulsory schooling at the age of seven years old. Hence, efficient approaches towards early identification and intervention through speedy diagnostic procedures for ASD are required. In recent years, advanced technologies like machine learning have been used to analyze and investigate ASD to improve diagnostic accuracy, time, and quality without complexity. These machine learning methods include artificial neural networks, support vector machines, a priori algorithms, and decision trees, most of which have been applied to datasets connected with autism to construct predictive models. Meanwhile, the selection of features remains an essential task before developing a predictive model for ASD classification. This review mainly investigates and analyzes up-to-date studies on machine learning methods for feature selection and classification of ASD. We recommend methods to enhance machine learning's speedy execution for processing complex data for conceptualization and implementation in ASD diagnostic research. This study can significantly benefit future research in autism using a machine learning approach for feature selection, classification, and processing imbalanced data.
    Matched MeSH terms: Language Therapy
  6. Zin NNINM, Rahimi WNAWM, Bakar NA
    Malays J Med Sci, 2019 Nov;26(6):19-34.
    PMID: 31908584 MyJurnal DOI: 10.21315/mjms2019.26.6.3
    Parasitic diseases represent one of the causes for significant global economic, environmental and public health impacts. The efficacy of currently available anti-parasitic drugs has been threatened by the emergence of single drug- or multidrug-resistant parasite populations, vector threats and high cost of drug development. Therefore, the discovery of more potent anti-parasitic drugs coming from medicinal plants such as Quercus infectoria is seen as a major approach to tackle the problem. A systematic review was conducted to assess the efficacy of Q. infectoria in treating parasitic diseases both in vitro and in vivo due to the lack of such reviews on the anti-parasitic activities of this plant. This review consisted of intensive searches from three databases including PubMed, Science Direct and Scopus. Articles were selected throughout the years, limited to English language and fully documented. A total of 454 potential articles were identified, but only four articles were accepted to be evaluated based on inclusion and exclusion criteria. Although there were insufficient pieces of evidence to account for the efficacy of Q. infectoria against the parasites, this plant appears to have anti-leishmanial, anti-blastocystis and anti-amoebic activities. More studies in vitro and in vivo are warranted to further validate the anti-parasitic efficacy of Q. infectoria.
    Matched MeSH terms: Language
  7. Ahmed MA, Zaidan BB, Zaidan AA, Salih MM, Lakulu MMB
    Sensors (Basel), 2018 Jul 09;18(7).
    PMID: 29987266 DOI: 10.3390/s18072208
    Loss of the ability to speak or hear exerts psychological and social impacts on the affected persons due to the lack of proper communication. Multiple and systematic scholarly interventions that vary according to context have been implemented to overcome disability-related difficulties. Sign language recognition (SLR) systems based on sensory gloves are significant innovations that aim to procure data on the shape or movement of the human hand. Innovative technology for this matter is mainly restricted and dispersed. The available trends and gaps should be explored in this research approach to provide valuable insights into technological environments. Thus, a review is conducted to create a coherent taxonomy to describe the latest research divided into four main categories: development, framework, other hand gesture recognition, and reviews and surveys. Then, we conduct analyses of the glove systems for SLR device characteristics, develop a roadmap for technology evolution, discuss its limitations, and provide valuable insights into technological environments. This will help researchers to understand the current options and gaps in this area, thus contributing to this line of research.
    Matched MeSH terms: Sign Language*
  8. Man MY, Ong MS, Mohamad MS, Deris S, Sulong G, Yunus J, et al.
    Malays J Med Sci, 2015 Dec;22(Spec Issue):9-19.
    PMID: 27006633 MyJurnal
    Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system.
    Matched MeSH terms: Language
  9. Lua Pei Lin, Nor Khaira Wahida Khairuzzaman
    MyJurnal
    Objective: This paper intended to review and analyse relevant published articles which have studied or applied multimedia as the educational medium for patients or their caregivers. The benefits were also recorded.

    Method: The search was performed across the databases EBSCO Host, Springer Link, Science Direct and PubMed for relevant studies. Only full-text articles using English as a language of publication were included. Eligible articles included any usage of multimedia intervention as health information delivery for patients or caregivers. No restriction for publication date was set to permit a wider capture.

    Result: Twenty articles met the inclusion criteria involving a total of 1,797 respondents. The studies have been conducted in various countries mostly in North American region followed by Europe. The focused disease for each study varied from asthma to cognitive impairment but most were on cancer. Problems in caregiving and depression were also reported. The overall data suggested that the multimedia-based education had generated modest improvement in self-efficacy, patient satisfaction, coping skills, and perceptions of social support. Cost benefits were also recorded. Additionally, patients’ behavioural changes were well maintained in parallel with the intervention programme.

    Conclusion: The evolution of multimedia as an educational medium is growing and its incorporation has benefited health education management especially in improving patients’ and their family’s psychosocial outcomes. However, due to still limited scientific evidence to support its value, further multimedia-based interventions should be developed out of the need to share information and knowledge among patients as well as caregivers.
    Matched MeSH terms: Language
  10. Mazumdar PK, Chaturvedi SK, Gopinath PS
    Psychopathology, 1995;28(4):185-9.
    PMID: 7480574
    A differential phenomenological study of acute and chronic schizophrenia is scanty. Thought disorder was assessed in 22 acute and 23 chronic schizophrenics. The scale for the assessment of thought, language and communication was used. Poverty of speech was significantly more frequent in acute schizophrenia. Positive formal thought disorder was unusually found to be severer in chronic schizophrenia. No other significant difference was found. From the perspective of thought disorder, acute and chronic forms of schizophrenia seem to be in a continuum with minimal difference.
    Matched MeSH terms: Schizophrenic Language
  11. Joginder Singh S, Iacono T, Gray KM
    Int J Speech Lang Pathol, 2011 Oct;13(5):389-98.
    PMID: 21888557 DOI: 10.3109/17549507.2011.603429
    The aim of this study was to explore the assessment, intervention, and family-centred practices of Malaysian and Australian speech-language pathologists (SLPs) when working with children with developmental disabilities who are pre-symbolic. A questionnaire was developed for the study, which was completed by 65 SLPs from Malaysia and 157 SLPs from Australia. Data reduction techniques were used prior to comparison of responses across questionnaire items. Results indicated that SLPs relied mostly on informal assessments. Malaysian and Australian SLPs differed significantly in terms of obtaining information from outside the clinic to inform assessment. When providing intervention, SLPs focused mostly on improving children's pre-verbal skills. A third of Australian SLPs listed the introduction of some form of symbolic communication as an early intervention goal, compared to only a small percentage of Malaysian SLPs. Regarding family involvement, SLPs most often involved mothers, with fathers and siblings being involved to a lesser extent. Overall, it appeared that practices of Malaysian SLPs had been influenced by developments in research, although there were some areas of service delivery that continued to rely on traditional models. Factors leading to similarities and differences in practice of SLPs from both countries as well as clinical and research implications of the study are discussed.
    Matched MeSH terms: Speech-Language Pathology/methods*
  12. Othman RM, Deris S, Illias RM
    J Biomed Inform, 2008 Feb;41(1):65-81.
    PMID: 17681495
    A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. Then, the parallel genetic algorithm is employed to perform batch retrieval and to accelerate the search in large search space of the Gene Ontology graph. The genetic similarity algorithm is implemented in the Gene Ontology browser named basic UTMGO to overcome the weaknesses of the existing Gene Ontology browsers which use a conventional approach based on keyword matching. To show the applicability of the basic UTMGO, we extend its structure to develop a Gene Ontology -based protein sequence annotation tool named extended UTMGO. The objective of developing the extended UTMGO is to provide a simple and practical tool that is capable of producing better results and requires a reasonable amount of running time with low computing cost specifically for offline usage. The computational results and comparison with other related tools are presented to show the effectiveness of the proposed algorithm and tools.
    Matched MeSH terms: Natural Language Processing
  13. Malaspinas AS, Westaway MC, Muller C, Sousa VC, Lao O, Alves I, et al.
    Nature, 2016 Oct 13;538(7624):207-214.
    PMID: 27654914 DOI: 10.1038/nature18299
    The population history of Aboriginal Australians remains largely uncharacterized. Here we generate high-coverage genomes for 83 Aboriginal Australians (speakers of Pama-Nyungan languages) and 25 Papuans from the New Guinea Highlands. We find that Papuan and Aboriginal Australian ancestors diversified 25-40 thousand years ago (kya), suggesting pre-Holocene population structure in the ancient continent of Sahul (Australia, New Guinea and Tasmania). However, all of the studied Aboriginal Australians descend from a single founding population that differentiated ~10-32 kya. We infer a population expansion in northeast Australia during the Holocene epoch (past 10,000 years) associated with limited gene flow from this region to the rest of Australia, consistent with the spread of the Pama-Nyungan languages. We estimate that Aboriginal Australians and Papuans diverged from Eurasians 51-72 kya, following a single out-of-Africa dispersal, and subsequently admixed with archaic populations. Finally, we report evidence of selection in Aboriginal Australians potentially associated with living in the desert.
    Matched MeSH terms: Language
  14. Lim YY, Prang KH, Cysique L, Pietrzak RH, Snyder PJ, Maruff P
    Behav Res Methods, 2009 Nov;41(4):1190-200.
    PMID: 19897828 DOI: 10.3758/BRM.41.4.1190
    Verbal memory tests-although important to the neuropsychological assessment of memory-are biased to many cultures. In the present article, we highlighted the limitations associated with the direct translation of tests and word matching, as well as the lack of ecological validity and cultural appropriateness when tests developed in one culture are used in another. To overcome these limitations, a verbal memory paradigm was developed that framed the memory assessment with a shopping-list format, but that developed culturally specific stimuli for the different language groups. The aim of the present study was to determine the equivalence of this shopping list memory test in different cultural and language groups. Eighty-three adults from English-, French-, Malay-, and Chinese-speaking cultures participated in four experiments. The results of all the experiments indicated that performance of verbal list learning is equivalent, irrespective of the language used. These results support the use of this methodology for minimizing cross-cultural test bias, and have important implications for testing culturally and linguistically diverse individuals.
    Matched MeSH terms: Language
  15. Rizwan Iqbal, Masrah Azrifah Azmi Murad
    MyJurnal
    Natural language interfaces to ontologies allow users to query the system using natural language queries.
    These systems take natural language query as input and transform it to formal query language equivalent
    to retrieve the desired information from ontologies. The existing natural language interfaces to ontologies
    offer support for handling negation queries; however, they offer limited support for dealing with them.
    This paper proposes a negation query handling engine which can handle relatively complex natural
    language queries than the existing systems. The proposed engine effectively understands the intent of
    the user query on the basis of a sophisticated algorithm, which is governed by a set of techniques and
    transformation rules. The proposed engine was evaluated using the Mooney data set and AquaLog dataset,
    and it manifested encouraging results.
    Matched MeSH terms: Language
  16. Mansur Z, Omar N, Tiun S, Alshari EM
    PLoS One, 2024;19(3):e0299652.
    PMID: 38512966 DOI: 10.1371/journal.pone.0299652
    As social media booms, abusive online practices such as hate speech have unfortunately increased as well. As letters are often repeated in words used to construct social media messages, these types of words should be eliminated or reduced in number to enhance the efficacy of hate speech detection. Although multiple models have attempted to normalize out-of-vocabulary (OOV) words with repeated letters, they often fail to determine whether the in-vocabulary (IV) replacement words are correct or incorrect. Therefore, this study developed an improved model for normalizing OOV words with repeated letters by replacing them with correct in-vocabulary (IV) replacement words. The improved normalization model is an unsupervised method that does not require the use of a special dictionary or annotated data. It combines rule-based patterns of words with repeated letters and the SymSpell spelling correction algorithm to remove repeated letters within the words by multiple rules regarding the position of repeated letters in a word, be it at the beginning, middle, or end of the word and the repetition pattern. Two hate speech datasets were then used to assess performance. The proposed normalization model was able to decrease the percentage of OOV words to 8%. Its F1 score was also 9% and 13% higher than the models proposed by two extant studies. Therefore, the proposed normalization model performed better than the benchmark studies in replacing OOV words with the correct IV replacement and improved the performance of the detection model. As such, suitable rule-based patterns can be combined with spelling correction to develop a text normalization model to correctly replace words with repeated letters, which would, in turn, improve hate speech detection in texts.
    Matched MeSH terms: Language
  17. Lim L, Ng TP, Ong AP, Tan MP, Cenina AR, Gao Q, et al.
    Alzheimers Res Ther, 2018 01 22;10(1):6.
    PMID: 29370825 DOI: 10.1186/s13195-017-0333-z
    BACKGROUND: Cognitive screeners are imperative for early diagnosis of dementia. The Visual Cognitive Assessment Test (VCAT) is a language-neutral, visual-based test which has proven useful for a multilingual population in a single-center study. However, its performance utility is unknown in a wider and more diverse Southeast Asian cohort.

    METHODS: We recruited 164 healthy controls (HC) and 120 cognitively impaired (CI) subjects- 47 mild cognitive impairment (MCI) and 73 mild Alzheimer's disease (AD) dementia participants, from four countries between January 2015 and August 2016 to determine the usefulness of a single version of the VCAT, without translation or adaptation, in a multinational, multilingual population. The VCAT was administered along with established cognitive evaluation.

    RESULTS: The VCAT, without local translation or adaptation, was effective in discriminating between HC and CI subjects (MCI and mild AD dementia). Mean (SD) VCAT scores for HC and CI subjects were 22.48 (3.50) and 14.17 (5.05) respectively. Areas under the curve for Montreal Cognitive Assessment (0.916, 95% CI 0.884-0.948) and the VCAT (0.905, 95% CI 0.870-0.940) in discriminating between HCs and CIs were comparable. The multiple languages used to administer VCAT in four countries did not significantly influence test scores.

    CONCLUSIONS: The VCAT without the need for language translation or cultural adaptation showed satisfactory discriminative ability and was effective in a multinational, multilingual Southeast Asian population.

    Matched MeSH terms: Language
  18. Sculthorpe-Petley L, Liu C, Hajra SG, Parvar H, Satel J, Trappenberg TP, et al.
    J Neurosci Methods, 2015 Apr 30;245:64-72.
    PMID: 25701685 DOI: 10.1016/j.jneumeth.2015.02.008
    Event-related potentials (ERPs) may provide a non-invasive index of brain function for a range of clinical applications. However, as a lab-based technique, ERPs are limited by technical challenges that prevent full integration into clinical settings.
    Matched MeSH terms: Language
  19. Barron D, Voracek M, Tran US, Ong HS, Morgan KD, Towell T, et al.
    Psychiatry Res, 2018 11;269:328-336.
    PMID: 30173038 DOI: 10.1016/j.psychres.2018.08.070
    The Schizotypal Personality Questionnaire (SPQ) is a widely-used self-report instrument for the assessment of schizotypal personality traits. However, the factor structure of scores on English and non-English translations of the SPQ has been a matter of debate. With little previous factorial evaluation of the German version of the SPQ (SPQ-G), we re-assessed the higher-order factor structure of the measure. A total of 2,428 German-speaking adults from Central Europe (CE) and the United Kingdom (UK) completed the SPQ-G. Confirmatory factor analysis - testing proposed 2-, 3-, and 4-factor models of SPQ-G scores - indicated that the 4-factor solution had best fit. Partial measurement invariance across cultural group (CE and UK) and sex was obtained for the 4-factor model. Further analyses showed CE participants had significantly higher scores than UK participants on one schizotypal facet. These results suggest that scores on the SPQ-G are best explained in terms of a higher-order, 4-factor solution in German migrant and non-migrant adults.
    Matched MeSH terms: Language
  20. Chai JT, Chen CJ
    MyJurnal
    Dyslexia is a language disorder that leads to difficulty with words and it is the most common type of learning disability. This article presents a systematic review on the current state of assistive technologies used in improving the learning process of learn-ers with dyslexia. A total of 25 journals articles and international conference papers published between 2000 and 2014 were included in the review. The research articles were collected from 12 databases and analyzed based on the qualitative cyclical pro-cess. A majority of the studies focused on children and adolescents. Four main themes on the types of technologies used in aiding the learning process of learners with dys-lexia are derived and discussed. These include text-to-speech, eye-tracking, virtual learning environments, and games. The text-to-speech technology is the most common type of technology used by learners with dyslexia. In terms of the roles played by the assistive technologies, another four emerging themes are identified, which cover the roles of aiding reading, writing, memory, and mathematics. The review also discovers that a majority of these studies focus on the use of technologies for improving the reading ability of learners with dyslexia.
    Matched MeSH terms: Language Disorders
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