Displaying publications 21 - 40 of 462 in total

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  1. A Bayesian-Inspired Item Response Theory-Based Framework to Produce Very Short Versions of MacArthur-Bates Communicative Development Inventories
    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. Tablet assessment of word comprehension reveals coarse word representations in 18-⁠20-month-old toddlers
    Lo CH, Rosslund A, Chai JH, Mayor J, Kartushina N
    Infancy, 2021 07;26(4):596-616.
    PMID: 33813801 DOI: 10.1111/infa.12401
    The present study explores the viability of using tablets in assessing early word comprehension by means of a two-alternative forced-choice task. Forty-nine 18-20-month-old Norwegian toddlers performed a touch-based word recognition task, in which they were prompted to identify the labeled target out of two displayed items on a touchscreen tablet. In each trial, the distractor item was either semantically related (e.g., dog-cat) or unrelated (e.g., dog-airplane) to the target. Our results show that toddlers as young as 18 months can engage meaningfully with a tablet-based assessment, with minimal verbal instruction and child-administrator interaction. Toddlers performed better in the semantically unrelated condition than in the related condition, suggesting that their word representations are still semantically coarse at this age. Furthermore, parental reports of comprehension, using the Norwegian version of the MacArthur-Bates Communicative Development Inventories, predicted toddlers' performance, with parent-child agreement stronger in the semantically unrelated condition, indicating that parents declare a word to be known by their child if it is understood at a coarse representational level. This study provides among the earliest evidence that remote data collection in 18-20 month-old toddlers is viable, as comparable results were observed from both in-laboratory and online administration of the touchscreen recognition task.
    Matched MeSH terms: Language Development*; Language Tests
  3. Case study of an Iranian-American neuropsychological assessment in the surgical setting: role of language and tests
    Ramezani A, Alvani SR, Lashai M, Rad H, Houshiarnejad A, Razani J, et al.
    Appl Neuropsychol Adult, 2019 12 27;29(1):53-58.
    PMID: 31880955 DOI: 10.1080/23279095.2019.1706517
    There is a growing need to conduct a neuropsychological assessment with bilingual Middle Eastern populations, particularly those who speak the Persian language (Farsi). Although validated neuropsychological and language tests have emerged in Iran, there remains a shortage of appropriate psychometric tests in the U.S. that have been validated for use with the Iranian-American population. This often leads to an assortment of using U.S. tests in English, U.S. tests translated into Farsi, and Iranian tests in Farsi, which can complicate the clinical assessment. To better understand common testing issues when working with bilingual Iranian-American patients, we review the first report of a 62-year-old, bilingual (English-Farsi) Iranian-American male with 18-years of education who was tested using U.S.-developed and Iranian-developed tests in both English and Farsi language. Pre-surgical, 6 months post-surgical, and 1.5 years of post-surgical assessment data are discussed. We highlight the strengths and limitations of naming tests, test used in the native country versus U.S. language tests, the importance of baseline testing, general bilingual Persian-English assessment considerations, and case-based learning points.
    Matched MeSH terms: Language*; Language Tests
  4. Fulltext Metaheuristics approach for maximum k satisfiability in restricted neural symbolic integration
    Sathasivam, Saratha, Mustafa Mamat, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor
    Pertanika Journal of Science & Technology, 2020;28(2):545-564.
    MyJurnal
    Maximum k Satisfiability logical rule (MAX-kSAT) is a language that bridges real life application to neural network optimization. MAX-kSAT is an interesting paradigm because the outcome of this logical rule is always negative/false. Hopfield Neural Network (HNN) is a type of neural network that finds the solution based on energy minimization. Interesting intelligent behavior has been observed when the logical rule is embedded in HNN. Increasing the storage capacity during the learning phase of HNN has been a challenging problem for most neural network researchers. Development of Metaheuristics algorithms has been crucial in optimizing the learning phase of Neural Network. The most celebrated metaheuristics model is Genetic Algorithm (GA). GA consists of several important operators that emphasize on solution improvement. Although GA has been reported to optimize logic programming in HNN, the learning complexity increases as the number of clauses increases. GA is more likely to be trapped in suboptimal fitness as the number of clauses increases. In this paper, metaheuristic algorithm namely Artificial Bee Colony (ABC) were proposed in learning MAX-kSAT programming. ABC is swarm-based metaheuristics that capitalized the capability of Employed Bee, Onlooker Bee, and Scout Bee. To this end, all the learning models were tested in a new restricted learning environment. Experimental results obtained from the computer simulation demonstrate the effectiveness of ABC in modelling MAX-kSAT.
    Matched MeSH terms: Language
  5. Fulltext Validation of inventory responses-oMR (IR-oMR) towards the self-assesment instrument of outdoor competency (OCL-oMR) among the co-curriculum center coaches in Malaysia
    Omar Firdaus Mohd Said, Md Amin Md Taff, Ahmad Hashim, Jaffry Zakaria
    Jurnal Sains Sukan & Pendidikan Jasmani, 2020;9(2):47-55.
    MyJurnal
    This study is fundamental in looking to validate the agreement of Self-Assesment Instrument of Outdoor Competency (OCL-oMR) among the Co-curriculum Center Coaches in Malaysia. The instrument are newly developed by the researcher . The Inventory Responses –oMR (IR-oMR) are purposely to evaluate and determine the goodness of self-assesement instrument of outdoor competency (OCL-oMR) among co-curriculum center coaches in Malaysia. By using the correlation & percentage, the analysis were used. N=10 of head coaches of co-curriculum Center were selected to be a sampels. These data is a secondary data that researcher used in the main research. But as a secondary data, its really important to researcher to identify and justify the newly instrument of self assesment of outdoor competency (OCL-oMR). Findings shown contents validity r=.82 were recorded and the language validity were shown r=.83. Meanwhile, anothers supporting data were used percentage of agreement of Inventory Responses –Omr (IR-oMR) toward the Self-Assesment Instrument of Outdoor Competency (OCL-oMR) among the Co-curriculum Center Coaches in Malaysia. Overall, from these findings, researcher found that’s the Inventory Responses – oMR (IR-oMR) shown that the Self-Assesment Instrument of Outdoor Competency (OCL-oMR) among the Co-curriculum Center Coaches in Malaysia are valid instrument to measure the competency level of outdoor education coaches in co-curriculum center in Malaysia and the Inventory Responses – oMR (IR-oMR) are significantly toward the outdoor competency (OCL-oMR).
    Matched MeSH terms: Language
  6. Fulltext Management of dysphagia by speech-language pathologists in Malaysia]. Pengendalian disfagia oleh patologis pertuturan-bahasa di Malaysia
    Sharma, Shobha, Haryani Harun, Rahayu Mustaffa Kamal, Srinovianti Noerdin
    Jurnal Sains Kesihatan Malaysia, 2006;4(2):39-51.
    MyJurnal
    This study in the management of dysphagia or swallowing disorders involved 72 contactable Speech-Language Pathologists (SLP) in Malaysia. A survey was undertaken to identify the patterns of dysphagia management by SLPs in Malaysia by identifying the percentage of SLPs in Malaysia who have managed swallowing disorders, the approximate number of patients, assessment and therapy techniques used, other professional involvement and the factors that influenced the confidence levels of the SLPs in managing swallowing disorders. Fifty percent (50%) of the forty four SLPs (61.6%) who responded to the survey had previously managed swallowing disorders. It was estimated that 5% (430 of 8268) of patients referred to the SLPs in Malaysia presented with dysphagia and were subsequently managed for their swallowing problems. The oromotor examination was carried out most frequently (100%) for evaluation of dysphagia while the compensatory technique proved to be the most frequently used management technique (77.3%). Most referrals to the SLPs were received from the neurosurgeon (59.1%); the otorhinolaryngologist was most referred to by the SLPs (50%). By using the Chi-squared analysis, it was found that clinical training in dysphagia at the undergraduate or post-graduate levels influenced the confidence levels of the SLPs in managing dysphagia cases (χ2 = 10.063 with p value = 0.007).
    Matched MeSH terms: Speech-Language Pathology
  7. Fulltext The treatment of phrasal verbs in bilingual learner dictionaries: implications on language learning
    Kamarudin, R., Moon, R.
    Journal of Academia Universiti Teknologi MARA Negeri Sembilan, 2018;6(1):120-128.
    MyJurnal
    The purpose of this study is to investigate how reference materials (i.e. dictionaries) commonly
    prescribed to Malaysian school learners address and describe a very common and important linguistic
    feature - phrasal verbs. Two bilingual learner dictionaries frequently recommended for secondary
    school learners in Malaysia were examined. Analysis of common phrasal verbs like pick up, come out,
    and go out was carried out by examining entries in the dictionaries that discuss this linguistic feature.
    Descriptive analysis was conducted to examine how this particular language form is described by
    looking at the selection of phrasal verbs, as well as information provided with respect to phrasal verbs.
    Results of the analysis have revealed some interesting findings with regard to the selection and
    description of phrasal verbs in these dictionaries, which may have also contributed to learners'
    difficulties in understanding and learning the language form. The paper will be concluded by
    discussing some recommendations with respect to the inclusion and selection of phrasal verbs in
    language reference materials particularly dictionaries in Malaysian schools.
    Matched MeSH terms: Language
  8. Fulltext Correction to: The antiangiogenic activities of ethanolic crude extracts of four Salvia species
    Zihlif M, Afifi F, Abu-Dahab R, Majid AMSA, Somrain H, Saleh MM, et al.
    BMC Complement Altern Med, 2018 02 16;18(1):64.
    PMID: 29452588 DOI: 10.1186/s12906-018-2126-8
    CORRECTION: After the publication [1] it came to the attention of the authors that one of the co-authors was incorrectly included as Hamza Somrain. The correct spelling is as follows: Hamzeh Sumrein.
    Matched MeSH terms: Language
  9. Fulltext The ecological discourse analysis of news discourse based on deep learning from the perspective of ecological philosophy
    Zhang B, Chandran Sandaran S, Feng J
    PLoS One, 2023;18(1):e0280190.
    PMID: 36696455 DOI: 10.1371/journal.pone.0280190
    Recently, ecological damage and environmental pollution have become increasingly serious. Experts in various fields have started to study related issues from diverse points of view. To prevent the accelerated deterioration of the ecological environment, ecolinguistics emerged. Eco-critical discourse analysis is one of the important parts of ecolinguistics research, that is, it is a critical discourse analysis of the use of language from the perspective of the language's ecological environment. Firstly, an ecological tone and modality system are constructed from an ecological perspective. Under the guidance of the ecological philosophy of "equality, harmony, and symbiosis", this study conducts an ecological discourse analysis on the Sino-US trade friction reports, aiming to present the similarities and differences between the two newspapers' trade friction discourses and to reveal the ecological significance of international ecological factors in the discourse. Secondly, this method establishes a vector expression of abstract words based on emotion dictionary resources and introduces emotion polarity and part-of-speech features of words. Then the word vector is formed into the text feature matrix, which is used as the input of the Convolutional Neural Network (CNN) model, and the Back Propagation algorithm is adopted to train the model. Finally, in the light of the trained CNN model, the unlabeled news is predicted, and the experimental results are analyzed. The results reveal that during the training process of Chinese and English datasets, the accuracy of the training set can reach nearly 100%, and the loss rate can be reduced to 0. On the test set, the classification accuracy of Chinese text can reach 83%, while that of English text can reach 90%, and the experimental results are ideal. This study provides an explanatory approach for ecological discourse analysis on the news reports of Sino-US trade frictions and has certain guiding significance for the comparative research on political news reports under different ideologies between China and the United States.
    Matched MeSH terms: Language
  10. Sentiment analysis of Indonesian tweets on COVID-19 and COVID-19 vaccinations
    Kalanjati VP, Hasanatuludhhiyah N, d'Arqom A, Arsyi DH, Marchianti ACN, Muhammad A, et al.
    F1000Res, 2023;12:1007.
    PMID: 38605817 DOI: 10.12688/f1000research.130610.3
    BACKGROUND: Sentiments and opinions regarding COVID-19 and the COVID-19 vaccination on Indonesian-language Twitter are scarcely reported in one comprehensive study, and thus were aimed at our study. We also analyzed fake news and facts, and Twitter engagement to understand people's perceptions and beliefs that determine public health literacy.

    METHODS: We collected 3,489,367 tweets data from January 2020 to August 2021. We analyzed factual and fake news using the string comparison method. The difflib library was used to measure similarity. The user's engagement was analyzed by averaging the engagement metrics of tweets, retweets, favorites, replies, and posts shared with sentiments and opinions regarding COVID-19 and COVID-19 vaccination.

    RESULT: Positive sentiments on COVID-19 and COVID-19 vaccination dominated, however, the negative sentiments increased during the beginning of the implementation of restrictions on community activities (PPKM).  The tweets were dominated by the importance of health protocols (washing hands, keeping distance, and wearing masks). Several types of vaccines were on top of the word count in the vaccine subtopic. Acceptance of the vaccination increased during the studied period, and the fake news was overweighed by the facts. The tweets were dynamic and showed that the engaged topics were changed from the nature of COVID-19 to the vaccination and virus mutation which peaked in the early and middle terms of 2021. The public sentiment and engagement were shifted from hesitancy to anxiety towards the safety and effectiveness of the vaccines, whilst changed again into wariness on an uprising of the delta variant.

    CONCLUSION: Understanding public sentiment and opinion can help policymakers to plan the best strategy to cope with the pandemic. Positive sentiments and fact-based opinions on COVID-19, and COVID-19 vaccination had been shown predominantly. However, sufficient health literacy levels could yet be predicted and sought for further study.

    Matched MeSH terms: Language
  11. Fulltext Effects of problem-based learning on EFL learning: A systematic review
    Guo Q, Jamil H, Ismail L, Luo S, Sun Z
    PLoS One, 2024;19(12):e0307819.
    PMID: 39666681 DOI: 10.1371/journal.pone.0307819
    Teaching English as a foreign language (EFL) is a priority globally, but pedagogical methods do not always keep up with the evolving needs of learners. Problem-based learning (PBL) is an innovative pedagogical approach that facilitates students' self-regulated learning, thereby improving their English proficiency. The present systematic literature review therefore concentrates on the application of PBL methodology in improving students' English language proficiency. It was conducted according to the systematic review and meta-analysis Preferred Reporting Items for Meta-Analyses (PRISMA) review methodology. In total, 27 articles related to PBL to improve English proficiency published between 2012 and 2023 were identified from Web of Science, Scopus, ProQuest, ERIC, and ScienceDirect databases. In the light of the findings, PBL has a positive effect on students' behaviour, academic performance, and critical thinking. Consequently, this paper contributes to policy makers, educators, and students to improve the English proficiency of students at all levels of education using PBL approach.
    Matched MeSH terms: Language
  12. Fulltext Comparison of reading speed with 3 different log-scaled reading charts
    Buari NH, Chen AH, Musa N
    J Optom, 2014 Oct-Dec;7(4):210-6.
    PMID: 25323642 DOI: 10.1016/j.optom.2013.12.009
    A reading chart that resembles real reading conditions is important to evaluate the quality of life in terms of reading performance. The purpose of this study was to compare the reading speed of UiTM Malay related words (UiTM-Mrw) reading chart with MNread Acuity Chart and Colenbrander Reading Chart.
    Matched MeSH terms: Language*
  13. Fulltext Word sense disambiguation using hybrid swarm intelligence approach
    Al-Saiagh W, Tiun S, Al-Saffar A, Awang S, Al-Khaleefa AS
    PLoS One, 2018;13(12):e0208695.
    PMID: 30571777 DOI: 10.1371/journal.pone.0208695
    Word sense disambiguation (WSD) is the process of identifying an appropriate sense for an ambiguous word. With the complexity of human languages in which a single word could yield different meanings, WSD has been utilized by several domains of interests such as search engines and machine translations. The literature shows a vast number of techniques used for the process of WSD. Recently, researchers have focused on the use of meta-heuristic approaches to identify the best solutions that reflect the best sense. However, the application of meta-heuristic approaches remains limited and thus requires the efficient exploration and exploitation of the problem space. Hence, the current study aims to propose a hybrid meta-heuristic method that consists of particle swarm optimization (PSO) and simulated annealing to find the global best meaning of a given text. Different semantic measures have been utilized in this model as objective functions for the proposed hybrid PSO. These measures consist of JCN and extended Lesk methods, which are combined effectively in this work. The proposed method is tested using a three-benchmark dataset (SemCor 3.0, SensEval-2, and SensEval-3). Results show that the proposed method has superior performance in comparison with state-of-the-art approaches.
    Matched MeSH terms: Language*
  14. Translation and Adaptation of the Diagnostic Criteria for Temporomandibular Disorders into the Malay Language: Psychometric Evaluation of Contents
    Tahir MKAM, Kadir K, Apipi M, Ismail SM, Yusof ZYM, Yap AU
    J Oral Facial Pain Headache, 2020 12 9;34(4):323-330.
    PMID: 33290438 DOI: 10.11607/ofph.2624
    AIMS: To develop the Malay DC/TMD through a formal cross-cultural adaptation (CCA) process for use in non-English speaking populations and to determine the reliability and validity of the Malay Graded Chronic Pain Scale (M-GCPS) and Malay Jaw Functional Limitation Scale (M-JFLS).

    METHODS: The English DC/TMD was translated into the Malay language using the forward-backward translation procedures specified in the INfORM guideline. The initial Malay instrument was pre-tested, and any discrepancies were identified and reconciled before producing the final Malay DC/TMD. Psychometric properties of the M-GCPS and M-JFLS were evaluated using a convenience sample of 252 subjects and were assessed using internal consistency and test-retest reliability, as well as face, content, concurrent, and construct validity testing. Internal consistency was assessed using Cronbach's alpha, while test-retest reliability was examined using intraclass correlation coefficient (ICC). Concurrent and construct validity of both domains were performed using Spearman ρ correlation test. In addition, construct and discriminant validity were appraised using Kruskal-Wallis and Mann-Whitney U tests, respectively.

    RESULTS: Cronbach's alpha values for the M-GCPS and M-JFLS were 0.95 and 0.97, respectively. The ICC was 0.98 for the M-GCPS and 0.99 for M-JFLS. The majority of the tested associations for both domains were found to be statistically significant, with good positive correlations.

    CONCLUSION: The M-GCPS and M-JFLS were found to be reproducible and valid. The Malay DC/TMD shows potential for use among Malay-speaking adults.

    Matched MeSH terms: Language*
  15. Fulltext PRELIMINARY STUDY ON E-HAILING DRIVERS NEEDS IN ENGLISH LANGUAGE LEARNING FOR THE PURPOSE OF SUCCESSFUL COMMUNICATION IN TOURISM INDUSTRY
    Shahazwan Mat Yusoff, Anwar Farhan Mohamad Marzaini, Siti Maftuhah Damio
    Journal of Academia Universiti Teknologi MARA Negeri Sembilan, 2021;9(1):14-20.
    MyJurnal
    E-hailing apps Grab and Uber have become household names, particularly among urbanites over these five years. Overall the consumer response to e-hailing services in Malaysia has been positive, with The Land Public Transport Commission (SPAD) reporting that 80% of consumers prefer e-hailing over taxis. As such, many believe the availability of e-hailing services will help to boost demand, and raise property prices and rentals and help the tourism sector in locations where they are available. As the demand grows, and tourists around the globe keep rising, the means of communication plays a vital role. Hence, this article explores the Grab drivers’ needs in English language learning for the purpose of successful communication in working environment. The needs are categorised into three elements: needs of English language at workplace, problems in English language usage, and preferences in learning English. A case study was carried out among 50 Grab drivers in Kuala Lumpur. The analysis of responses to the needs in English language learning among Grab drivers is hoped to fashion English language course or the syllabus to the e- hailing drivers.
    Matched MeSH terms: Language; Language Development
  16. Mobile-assisted and gamification-based language learning: a systematic literature review
    Ishaq K, Mat Zin NA, Rosdi F, Jehanghir M, Ishaq S, Abid A
    PeerJ Comput Sci, 2021;7:e496.
    PMID: 34084920 DOI: 10.7717/peerj-cs.496
    Learning a new language is a challenging task. In many countries, students are encouraged to learn an international language at school level. In particular, English is the most widely used international language and is being taught at the school level in many countries. The ubiquity and accessibility of smartphones combined with the recent developments in mobile application and gamification in teaching and training have paved the way for experimenting with language learning using mobile phones. This article presents a systematic literature review of the published research work in mobile-assisted language learning. To this end, more than 60 relevant primary studies which have been published in well-reputed venues have been selected for further analysis. The detailed analysis reveals that researchers developed many different simple and gamified mobile applications for learning languages based on various theories, frameworks, and advanced tools. Furthermore, the study also analyses how different applications have been evaluated and tested at different educational levels using different experimental settings while incorporating a variety of evaluation measures. Lastly, a taxonomy has been proposed for the research work in mobile-assisted language learning, which is followed by promising future research challenges in this domain.
    Matched MeSH terms: Language; Language Development
  17. Fulltext Intelligent Malaysian Sign Language Translation System Using Convolutional-Based Attention Module with Residual Network
    Khan RU, Khattak H, Wong WS, AlSalman H, Mosleh MAA, Mizanur Rahman SM
    Comput Intell Neurosci, 2021;2021:9023010.
    PMID: 34925497 DOI: 10.1155/2021/9023010
    The deaf-mutes population always feels helpless when they are not understood by others and vice versa. This is a big humanitarian problem and needs localised solution. To solve this problem, this study implements a convolutional neural network (CNN), convolutional-based attention module (CBAM) to recognise Malaysian Sign Language (MSL) from images. Two different experiments were conducted for MSL signs, using CBAM-2DResNet (2-Dimensional Residual Network) implementing "Within Blocks" and "Before Classifier" methods. Various metrics such as the accuracy, loss, precision, recall, F1-score, confusion matrix, and training time are recorded to evaluate the models' efficiency. The experimental results showed that CBAM-ResNet models achieved a good performance in MSL signs recognition tasks, with accuracy rates of over 90% through a little of variations. The CBAM-ResNet "Before Classifier" models are more efficient than "Within Blocks" CBAM-ResNet models. Thus, the best trained model of CBAM-2DResNet is chosen to develop a real-time sign recognition system for translating from sign language to text and from text to sign language in an easy way of communication between deaf-mutes and other people. All experiment results indicated that the "Before Classifier" of CBAMResNet models is more efficient in recognising MSL and it is worth for future research.
    Matched MeSH terms: Sign Language*
  18. The national identity on the border: Indonesian language awareness and attitudes through multi-ethnic community involvement
    Martono M, Dewantara JA, Efriani E, Prasetiyo WH
    J Community Psychol, 2022 01;50(1):111-125.
    PMID: 33465246 DOI: 10.1002/jcop.22505
    State borders are the areas that are vulnerable to the degradation of national identity. The purpose of this study was to investigate the attitudes and the behavior of language use among the multi-ethnic Indonesian of predominantly Dayak, Malay, and Chinese who resided on the Indonesia-Malaysia border. The present research applied a qualitative ethnographic approach to document and to describe how a group of multi-ethnic communities participated in building their awareness, attitudes and practices of language as a national identity. The data were taken from 20 informants. They were teachers, students, local people, entrepreneurs, and state civil apparatus. The research found out that the ethnic groups on the border were highly aware of using Indonesian language as evidenced through a form of community involvement, volunteerism and social attitudes in civilizing Indonesian as the dominant language at the border. Their awareness was shown through their involvement, volunteerism, and social attitudes in developing Indonesian language as the dominant language in the border. It is argued that the involvement of all ethnic groups on the border affects positively on strengthening their attitudes and awareness in using Indonesian language.
    Matched MeSH terms: Language*
  19. Fulltext Insights into the demographic history of Asia from common ancestry and admixture in the genomic landscape of present-day Austroasiatic speakers
    Tagore D, Aghakhanian F, Naidu R, Phipps ME, Basu A
    BMC Biol, 2021 03 29;19(1):61.
    PMID: 33781248 DOI: 10.1186/s12915-021-00981-x
    BACKGROUND: The demographic history of South and Southeast Asia (S&SEA) is complex and contentious, with multiple waves of human migration. Some of the earliest footfalls were of the ancestors of modern Austroasiatic (AA) language speakers. Understanding the history of the AA language family, comprising of over 150 languages and their speakers distributed across broad geographical region in isolated small populations of various sizes, can help shed light on the peopling of S&SEA. Here we investigated the genetic relatedness of two AA groups, their relationship with other ethno-linguistically distinct populations, and the relationship of these groups with ancient genomes of individuals living in S&SEA at different time periods, to infer about the demographic history of this region.

    RESULTS: We analyzed 1451 extant genomes, 189 AAs from India and Malaysia, and 43 ancient genomes from S&SEA. Population structure analysis reveals neither language nor geography appropriately correlates with genetic diversity. The inconsistency between "language and genetics" or "geography and genetics" can largely be attributed to ancient admixture with East Asian populations. We estimated a pre-Neolithic origin of AA language speakers, with shared ancestry between Indian and Malaysian populations until about 470 generations ago, contesting the existing model of Neolithic expansion of the AA culture. We observed a spatio-temporal transition in the genetic ancestry of SEA with genetic contribution from East Asia significantly increasing in the post-Neolithic period.

    CONCLUSION: Our study shows that contrary to assumptions in many previous studies and despite having linguistic commonality, Indian AAs have a distinct genomic structure compared to Malaysian AAs. This linguistic-genetic discordance is reflective of the complex history of population migration and admixture shaping the genomic landscape of S&SEA. We postulate that pre-Neolithic ancestors of today's AAs were widespread in S&SEA, and the fragmentation and dissipation of the population have largely been a resultant of multiple migrations of East Asian farmers during the Neolithic period. It also highlights the resilience of AAs in continuing to speak their language in spite of checkered population distribution and possible dominance from other linguistic groups.

    Matched MeSH terms: Language*
  20. Fulltext Natural language processing in narrative breast radiology reporting in University Malaya Medical Centre
    Tan WM, Ng WL, Ganggayah MD, Hoe VCW, Rahmat K, Zaini HS, et al.
    Health Informatics J, 2023;29(3):14604582231203763.
    PMID: 37740904 DOI: 10.1177/14604582231203763
    Radiology reporting is narrative, and its content depends on the clinician's ability to interpret the images accurately. A tertiary hospital, such as anonymous institute, focuses on writing reports narratively as part of training for medical personnel. Nevertheless, free-text reports make it inconvenient to extract information for clinical audits and data mining. Therefore, we aim to convert unstructured breast radiology reports into structured formats using natural language processing (NLP) algorithm. This study used 327 de-identified breast radiology reports from the anonymous institute. The radiologist identified the significant data elements to be extracted. Our NLP algorithm achieved 97% and 94.9% accuracy in training and testing data, respectively. Henceforth, the structured information was used to build the predictive model for predicting the value of the BIRADS category. The model based on random forest generated the highest accuracy of 92%. Our study not only fulfilled the demands of clinicians by enhancing communication between medical personnel, but it also demonstrated the usefulness of mineable structured data in yielding significant insights.
    Matched MeSH terms: Natural Language Processing*
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