Author(s): Paquette A; Byers-Heinlein K;

Language mixing is a common feature of bilingual communication, yet its predictors and effects on children's vocabulary development remain debated. Most research has been conducted in contexts with clear societal and heritage languages, leaving open questions about language mixing in environments with two societal languages. Montreal provides a unique ...

Article GUID: 41153161

Author(s): Jafarpour H; Wu G; Cheligeer CK; Yan J; Xu Y; Southern DA; Eastwood CA; Zeng Y; Quan H;

Background: Narrative electronic medical records (EMR), which include textual notes created by clinicians within healthcare environments, represent a significant resource for documenting various facets of patient care. This form of text exhibits distinctive characteristics, such as the occurrence of grammatically incorrect sentences, abbreviations, freque ...

Article GUID: 41072367

Author(s): Kalenkovich E; Koorathota S; Tor S; Amatuni A; Egan-Dailey S; Moore C; Laing C; Garrison H; Baudet G; Bulgarelli F; Uner S; Righter L; Bergelson E;

This paper describes a dataset consisting of manually annotated nouns from a corpus of longitudinal day-long audio and hour-long video recordings collected monthly from 44 babies from age 6 months to age 17 months. This dataset was created as part of a larger project, called SEEDLingS, that exami ...

Article GUID: 41034519

Author(s): Zou H; Wang Y; Huang A;

Fine-grained aspect-based sentiment analysis requires language models to identify aspect entities and the corresponding sentiment information in the input text content. Transformer-based pre-trained large language models have demonstrated remarkable performance on various challenging natural language processing tasks. However, large language models face l ...

Article GUID: 40876298

Author(s): Koleilat T; Asgariandehkordi H; Rivaz H; Xiao Y;

Segmentation of anatomical structures and pathologies in medical images is essential for modern disease diagnosis, clinical research, and treatment planning. While significant advancements have been made in deep learning-based segmentation techniques, many of these methods still suffer from limitations in data efficiency, generalizability, and interactivi ...

Article GUID: 40779830

Author(s): Nadler EO; Guilbeault D; Ringold SM; Williamson TR; Bellemare-Pepin A; Com?a IM; Jerbi K; Narayanan S; Aziz-Zadeh L;

Can metaphorical reasoning involving embodied experience-such as color perception-be learned from the statistics of language alone? Recent work finds that colorblind individuals robustly understand and reason abstractly about color, implying that color associations in everyday language might cont ...

Article GUID: 40621800

Author(s): Quirk E; Hadeed N; Byers-Heinlein K;

Family language strategies are approaches that parents adopt for language use with their multilingual children. In bilingual contexts, these strategies influence children's language exposure and development (Macleod et al., 2022). In the more complex context of trilingualism, how families settle on strategies and their relationship with exposure may d ...

Article GUID: 40443954

Author(s): Pellerin S; Houzé B; Bedetti C; Phillips N; Brambati SM;

BackgroundMild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease (AD) for many individuals, is accompanied by widespread connected speech (CS) changes (e.g., shorter CS samples, mention of fewer semantic content units, lower syntactic complexity). Nevertheless, findings on CS in MCI are heterogeneous. This heterogeneity, combined wi ...

Article GUID: 40232260

Author(s): Stanley J; Rabot E; Reddy S; Belilovsky E; Mottron L; Bzdok D;

Efforts to use genome-wide assays or brain scans to diagnose autism have seen diminishing returns. Yet the clinical intuition of healthcare professionals, based on longstanding first-hand experience, remains the gold standard for diagnosis of autism. We leveraged deep learning to deconstruct and interrogate the logic of expert clinician intuition from cli ...

Article GUID: 40147442

Author(s): Cheligeer C; Southern DA; Yan J; Wu G; Pan J; Lee S; Martin EA; Jafarpour H; Eastwood CA; Zeng Y; Quan H;

Objectives: Adverse event detection from Electronic Medical Records (EMRs) is challenging due to the low incidence of the event, variability in clinical documentation, and the complexity of data formats. Pulmonary embolism as an adverse event (PEAE) is particularly difficult to identify using exi ...

Article GUID: 40105654

Author(s): Moore C; Williams ME; Byers-Heinlein K;

Previous research suggests that monolingual children learn words more readily in contexts with referential continuity (i.e., repeated labeling of the same referent) than in contexts with referential discontinuity (i.e., referent switches). Here, we extended this work by testing monolingual and bilingual 3- and 4-year-olds' (N = 64) novel word learning ...

Article GUID: 39798202