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1
When forgetting fosters learning: A neural network model for Statistical Learning
Endress, A.; Johnson, S.. - : Elsevier, 2021
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2
kwu_sqwa?qwa?alx (We begin to speak): Our Journey within Nsyilxcn (Okanagan) Language Revitalization ...
Johnson S?Imla?Xw, Michele K.. - : Canadian Journal of Native Education, 2021
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3
Statistical learning and memory
Endress, A.; Slone, L. K.; Johnson, S. P.. - : Elsevier, 2020
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4
Performance of the German version of the PARCA-R questionnaire as a developmental screening tool in two-year-old very preterm infants.
In: PloS one, vol. 15, no. 9, pp. e0236289 (2020)
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5
Standardisation of the Parent Report of Children’s Abilities-Revised (PARCA-R): a norm-referenced assessment of cognitive and language development at 2 years of age.
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6
Speaking my patient's language: bilingual nurses’ perspective about provision of language concordant care to patients with limited English proficiency
Ali, P.A.; Johnson, S.. - : Wiley, 2017
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7
Use of spatial communication in aphasia
Johnson, S.; Dipper, L.; Cocks, Naomi. - : Informa Healthcare, 2013
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8
Use of Spatial Communication in Aphasia
Dipper, L.; Johnson, S.; Cocks, N.. - : WILEY-BLACKWELL, 2013
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9
Embedding communication and literacy in the curriculum
In: Alexander, P., Briguglio, C., Johnson, S., Pearce, J. <https://researchrepository.murdoch.edu.au/view/author/Pearce, Jane.html>, Veitch, S. <https://researchrepository.murdoch.edu.au/view/author/Veitch, Sarah.html>, Barrett-Lennard, S. and Harvey, E. (2013) Embedding communication and literacy in the curriculum. In: Teaching and Learning Forum 2013: Design, develop, evaluate - The core of the learning environment, 7 - 8 February 2013, Murdoch University, Murdoch, W.A. (2013)
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10
Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.
In: PLOS Computational Biology, vol. 9, no. 4, pp. e1002987 (2013)
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11
Educational outcomes in extremely preterm children: neuropsychological correlates and predictors of attainment.
In: PubMed ; http://www.ncbi.nlm.nih.gov/pubmed/ (2012)
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12
Relationship between test scores using the second and third editions of the Bayley Scales in extremely preterm children.
In: PubMed ; http://www.ncbi.nlm.nih.gov/pubmed/ (2012)
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13
Relationship between test scores using the second and third editions of the Bayley Scales in extremely preterm children.
In: J Pediatr , 160 (4) 553 - 558. (2012) (2012)
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14
The bayley-III cognitive and language scales: how do scores relate to the bayley ii?
Moore, T; Johnson, S; Haider, S. - : BMJ Publishing Group Ltd, 2011
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15
Early Indications of Delayed Cognitive Development in Preschool Children Born very Preterm: Evidence from Domain-General and Domain-Specific Tasks
In: INFANT CHILD DEV , 20 (4) 400 - 422. (2011) (2011)
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16
Educational Outcomes in Extremely Preterm Children: Neuropsychological Correlates and Predictors of Attainment
In: DEV NEUROPSYCHOL , 36 (1) 74 - 95. (2011) (2011)
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17
Inglese: S. Johnson, Return of carry trade investors hits yen
Reggiani, Enrico (orcid:0000-0003-2101-7824). - : country:ITA, 2006
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18
Comparing syntactic complexity in medical and non-medical corpora.
Campbell, D. A.; Johnson, S. B.. - : American Medical Informatics Association, 2001
Abstract: With the growing use of Natural Language Processing (NLP) techniques as solutions in Medical Informatics, the need to quickly and efficiently create the knowledge structures used by these systems has grown concurrently. Automatic discovery of a lexicon for use by an NLP system through machine learning will require information about the syntax of medical language. Understanding the syntactic differences between medical and non-medical corpora may allow more efficient acquisition of a lexicon. Three experiments designed to quantify the syntactic differences in medical and non-medical corpora were conducted. The results show that the syntax of medical language shows less variation than non-medical language and is likely simpler. The differences were great enough to question the applicability of general language tools on medical language. These differences may reduce the difficulty of some free text machine learning problems by capitalizing on the simpler nature of narrative medical syntax.
Keyword: Research Article
URL: http://www.ncbi.nlm.nih.gov/pubmed/11825160
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2243419
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19
Evaluating the UMLS as a source of lexical knowledge for medical language processing.
Friedman, C.; Liu, H.; Shagina, L.. - : American Medical Informatics Association, 2001
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20
A technique for semantic classification of unknown words using UMLS resources.
Campbell, D. A.; Johnson, S. B.. - : American Medical Informatics Association, 1999
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