2,454 research outputs found

    The Generalizability of Machine Learning Models of Personality across Two Text Domains

    No full text
    Machine learning of high-dimensional models have received attention for their ability to predict psychological variables, such as personality. However, it has been less examined to what degree such models are capable of generalizing across domains. Across two text domains (Reddit message and personal essays), compared to low-dimensional- and theoretical models, atheoretical high-dimensional models provided superior predictive accuracy within but poor/non-significant predictive accuracy across domains. Thus, complex models depended more on the specifics of the trained domain. Further, when examining predictors of models, few survived across domains. We argue that theory remains important when conducting prediction-focused studies and that research on both high- and low-dimensional models benefit from establishing conditions under which they generalize

    Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness

    Get PDF
    BackgroundIncreased data availability has prompted the creation of clinical decision support systems. These systems utilise clinical information to enhance health care provision, both to predict the likelihood of specific clinical outcomes or evaluate the risk of further complications. However, their adoption remains low due to concerns regarding the quality of recommendations, and a lack of clarity on how results are best obtained and presented.MethodsWe used autoencoders capable of reducing the dimensionality of complex datasets in order to produce a 2D representation denoted as latent space to support understanding of complex clinical data. In this output, meaningful representations of individual patient profiles are spatially mapped in an unsupervised manner according to their input clinical parameters. This technique was then applied to a large real-world clinical dataset of over 12,000 patients with an illness compatible with dengue infection in Ho Chi Minh City, Vietnam between 1999 and 2021. Dengue is a systemic viral disease which exerts significant health and economic burden worldwide, and up to 5% of hospitalised patients develop life-threatening complications.ResultsThe latent space produced by the selected autoencoder aligns with established clinical characteristics exhibited by patients with dengue infection, as well as features of disease progression. Similar clinical phenotypes are represented close to each other in the latent space and clustered according to outcomes broadly described by the World Health Organisation dengue guidelines. Balancing distance metrics and density metrics produced results covering most of the latent space, and improved visualisation whilst preserving utility, with similar patients grouped closer together. In this case, this balance is achieved by using the sigmoid activation function and one hidden layer with three neurons, in addition to the latent dimension layer, which produces the output (Pearson, 0.840; Spearman, 0.830; Procrustes, 0.301; GMM 0.321).ConclusionThis study demonstrates that when adequately configured, autoencoders can produce two-dimensional representations of a complex dataset that conserve the distance relationship between points. The output visualisation groups patients with clinically relevant features closely together and inherently supports user interpretability. Work is underway to incorporate these findings into an electronic clinical decision support system to guide individual patient management.</jats:sec

    Expression of targets of the RNA-binding protein AUF-1 in human airway epithelium indicates its role in cellular senescence and inflammation

    Get PDF
    INTRODUCTION: The RNA-binding protein AU-rich-element factor-1 (AUF-1) participates to posttranscriptional regulation of genes involved in inflammation and cellular senescence, two pathogenic mechanisms of chronic obstructive pulmonary disease (COPD). Decreased AUF-1 expression was described in bronchiolar epithelium of COPD patients versus controls and in vitro cytokine- and cigarette smoke-challenged human airway epithelial cells, prompting the identification of epithelial AUF-1-targeted transcripts and function, and investigation on the mechanism of its loss. RESULTS: RNA immunoprecipitation-sequencing (RIP-Seq) identified, in the human airway epithelial cell line BEAS-2B, 494 AUF-1-bound mRNAs enriched in their 3'-untranslated regions for a Guanine-Cytosine (GC)-rich binding motif. AUF-1 association with selected transcripts and with a synthetic GC-rich motif were validated by biotin pulldown. AUF-1-targets' steady-state levels were equally affected by partial or near-total AUF-1 loss induced by cytomix (TNFα/IL1β/IFNγ/10 nM each) and siRNA, respectively, with differential transcript decay rates. Cytomix-mediated decrease in AUF-1 levels in BEAS-2B and primary human small-airways epithelium (HSAEC) was replicated by treatment with the senescence- inducer compound etoposide and associated with readouts of cell-cycle arrest, increase in lysosomal damage and senescence-associated secretory phenotype (SASP) factors, and with AUF-1 transfer in extracellular vesicles, detected by transmission electron microscopy and immunoblotting. Extensive in-silico and genome ontology analysis found, consistent with AUF-1 functions, enriched RIP-Seq-derived AUF-1-targets in COPD-related pathways involved in inflammation, senescence, gene regulation and also in the public SASP proteome atlas; AUF-1 target signature was also significantly represented in multiple transcriptomic COPD databases generated from primary HSAEC, from lung tissue and from single-cell RNA-sequencing, displaying a predominant downregulation of expression. DISCUSSION: Loss of intracellular AUF-1 may alter posttranscriptional regulation of targets particularly relevant for protection of genomic integrity and gene regulation, thus concurring to airway epithelial inflammatory responses related to oxidative stress and accelerated aging. Exosomal-associated AUF-1 may in turn preserve bound RNA targets and sustain their function, participating to spreading of inflammation and senescence to neighbouring cells

    Mortality and Sequential Organ Failure Assessment Score in Patients With Suspected Sepsis: The Impact of Acute and Preexisting Organ Failures and Infection Likelihood

    No full text
    IMPORTANCE:. The Sequential Organ Failure Assessment (SOFA) was chosen in the definition of sepsis due to superior validity in predicting mortality. However, few studies have assessed the contributions of acute versus chronic organ failures to SOFA for mortality prediction. OBJECTIVES:. The main objective in this study was to assess the relative importance of chronic and acute organ failures in mortality prediction in patients with suspected sepsis at hospital admission. We also evaluated how the presence of infection influenced the ability of SOFA to predict 30-day mortality. DESIGN, SETTING, AND PARTICIPANTS:. Single-center prospective cohort study including 1,313 adult patients with suspected sepsis in rapid response teams in the emergency department. MAIN OUTCOMES AND MEASURES:. The main outcome was 30-day mortality. We measured the maximum total SOFA score during admission (SOFATotal), whereas preexisting chronic organ failure SOFA (SOFAChronic) score was assessed by chart review, allowing calculation of the corresponding acute SOFA (SOFAAcute) score. Likelihood of infection was determined post hoc as “No infection” or “Infection.” RESULTS:. SOFAAcute and SOFAChronic were both associated with 30-day mortality, adjusted for age and sex (adjusted odds ratios [AORs], 1.3; 95% CI, 1.3–14 and 1.3; 1.2–1.7), respectively. Presence of infection was associated with lower 30-day mortality (AOR, 0.4; 95% CI, 0.2–0.6), even when corrected for SOFA. In “No infection” patients, SOFAAcute was not associated with mortality (AOR, 1.1; 95% CI, 1.0–1.2), and in this subgroup, neither SOFAAcute greater than or equal to 2 (relative risk [RR], 1.1; 95% CI, 0.6–1.8) nor SOFATotal greater than or equal to 2 (RR, 3.6; 95% CI, 0.9–14.1) was associated with higher mortality. CONCLUSIONS AND RELEVANCE:. Chronic and acute organ failures were equally associated with 30-day mortality in suspected sepsis. A substantial part of the total SOFA score was due to chronic organ failure, calling for caution when using total SOFA in defining sepsis and as an outcome in intervention studies. SOFA’s mortality prediction ability was highly dependent on actual presence of infection

    PY-03 The Effect of Notifications on Different Levels of Processing of Memory

    No full text
    Memory is a process that involves the acquiring, encoding, storing, and retrieving of information obtained from the environment. According to the levels of processing theory, proposed by Craik and Lockhart, the perception of stimuli requires analysis at various cognitive levels (1972). Processing things at greater “depth” involves more cognitive analysis and making connections with already known material. This deeper analysis is associated with longer retention and better performance on memory recall tasks (Craik & Lockhart, 1972). To process the presence of a stimulus, you must first attend to it. According to Mulligan, divided attention results in worse performance on semantic memory recall tasks (1998). This is likely due to the load theory of attention; this theory states that processing capacity, how much information input a person can handle at one time, is limited (Lavie, 2004). The perceptual load, the difficulty of a given task, varies between different actions; high-load tasks, such as reading, use up more cognitive resources than low-load tasks, thereby they use more processing capacity (Lavie, 2004; Stothart et al., 2015). Overall, dividing attention between multiple stimuli prevents individuals from fully focusing on and processing the “to-be-remembered” information, which can be especially harmful in an academic setting. Unfortunately, distractions in the academic environment are nearly impossible to avoid on college campuses with the accessibility of cell phones. A study by Dietz and Henrich concluded that texting during class resulted in significantly worse performance on semantic memory recall and recognition tasks (2014). What many students fail to realize is that these notifications cause distractions far after the *bing* noise stops; cell phone notifications promote task-irrelevant thoughts and prevent students from focusing on the material. Even when students ignored the notification, their performance on semantic memory recall tasks decreased (Stothart et al., 2015). This experiment will test the effect of cell phone notifications at different levels of cognitive processing (deep vs. shallow) on semantic memory recall and recognition. After the level of processing task is complete, a memory recall and recognition task will be given to assess how much the presence (or lack thereof) of a cell phone notification disrupted processing. It is hypothesized that the presence of notifications in both shallow and deep processing will decrease memory performance. However, the presence of notifications during deep processing should have a greater decrease due to the high perceptual load this task requires, which will be interrupted by the cell phone notification

    Impact of Insurance Payer on Stage at Diagnosis of Prostate Cancer

    No full text
    Objectives: Prostate cancer (CaP) is the most common site of cancer in men in the United States and is very treatable when diagnosed in localized and regional stages. While there are widely available forms of screening that can detect CaP in its early stages, factors that can affect healthcare access such as health insurance, race, and Appalachian residency have been linked with differences in rates of distant-stage CaP diagnosis. This study aimed to explore the relationships between health insurance, race, Appalachian residency, and late-stage CaP diagnosis in the state of Kentucky. Methods: A sample of 26,622 men from the state of Kentucky collected between January 1st, 2011 and December 31st, 2020 was analyzed using data collected by the Kentucky Cancer Registry. Bivariate and multivariate analyses were conducted to examine the relationships between these variables and stage at diagnosis. Results: Significant bivariate associations were found between late-stage diagnosis and age (p\u3c0.0001), race (p=0.0147), Appalachian residency (p=0.0007), and primary insurance payer (p\u3c0.0001). In the logistic regression analysis, increasing age (AOR: 1.070 per year), being a Black man (AOR: 1.477 compared with White/Unknown/Other) being uninsured (AOR: 5.054 compared with privately insured), using Medicaid (AOR: 4.198), using Medicare (AOR: 1.598), and Appalachian residency (AOR: 1.131 compared with non-Appalachian residents) were all significantly associated with having higher odds of receiving a late-stage CaP diagnosis. Conclusions: All of the variables analyzed were significantly associated with differences in odds of late-stage CaP diagnoses, with people who are uninsured and Medicaid-users having the largest increase in odds. The identification of these barriers to healthcare and the mechanisms by which they work is a vital step in crafting policy that can better address these disparities

    Learning meaningful latent space representations for patient risk stratification: model development and validation for dengue and other acute febrile illness

    Get PDF
    Background: Increased data availability has prompted the creation of clinical decision support systems. These systems utilise clinical information to enhance health care provision, both to predict the likelihood of specific clinical outcomes or evaluate the risk of further complications. However, their adoption remains low due to concerns regarding the quality of recommendations, and a lack of clarity on how results are best obtained and presented. Methods: We used autoencoders capable of reducing the dimensionality of complex datasets in order to produce a 2D representation denoted as latent space to support understanding of complex clinical data. In this output, meaningful representations of individual patient profiles are spatially mapped in an unsupervised manner according to their input clinical parameters. This technique was then applied to a large real-world clinical dataset of over 12,000 patients with an illness compatible with dengue infection in Ho Chi Minh City, Vietnam between 1999 and 2021. Dengue is a systemic viral disease which exerts significant health and economic burden worldwide, and up to 5% of hospitalised patients develop life-threatening complications. Results: The latent space produced by the selected autoencoder aligns with established clinical characteristics exhibited by patients with dengue infection, as well as features of disease progression. Similar clinical phenotypes are represented close to each other in the latent space and clustered according to outcomes broadly described by the World Health Organisation dengue guidelines. Balancing distance metrics and density metrics produced results covering most of the latent space, and improved visualisation whilst preserving utility, with similar patients grouped closer together. In this case, this balance is achieved by using the sigmoid activation function and one hidden layer with three neurons, in addition to the latent dimension layer, which produces the output (Pearson, 0.840; Spearman, 0.830; Procrustes, 0.301; GMM 0.321). Conclusion: This study demonstrates that when adequately configured, autoencoders can produce two-dimensional representations of a complex dataset that conserve the distance relationship between points. The output visualisation groups patients with clinically relevant features closely together and inherently supports user interpretability. Work is underway to incorporate these findings into an electronic clinical decision support system to guide individual patient management

    River Cities Network Series - Symposium Video 1.m4v

    No full text
    Video used to simulate how augmneted reality might be implemented as site specific installations. This video was presented in the first River Cities Network Symposium for Vietnam projects, hosted by RMIT Vietnam, 08/04/2023. The project has been seed funded by RMIT Vietnam, to establish the viability of the project, and to assess its impact in the community and in the tourism sector.</p

    Rethinking the American National Narratives: Finding a way forward with our past and with hope

    Get PDF
    An essay contributing to the ongoing conversation about America\u27s national narratives through an analysis of how stories shape our country and the steps we can take towards a more inclusive, hope-based narrative

    Expression of targets of the RNA-binding protein AUF-1 in human airway epithelium indicates its role in cellular senescence and inflammation

    Get PDF
    IntroductionThe RNA-binding protein AU-rich-element factor-1 (AUF-1) participates to posttranscriptional regulation of genes involved in inflammation and cellular senescence, two pathogenic mechanisms of chronic obstructive pulmonary disease (COPD). Decreased AUF-1 expression was described in bronchiolar epithelium of COPD patients versus controls and in vitro cytokine- and cigarette smoke-challenged human airway epithelial cells, prompting the identification of epithelial AUF-1-targeted transcripts and function, and investigation on the mechanism of its loss. ResultsRNA immunoprecipitation-sequencing (RIP-Seq) identified, in the human airway epithelial cell line BEAS-2B, 494 AUF-1-bound mRNAs enriched in their 3'-untranslated regions for a Guanine-Cytosine (GC)-rich binding motif. AUF-1 association with selected transcripts and with a synthetic GC-rich motif were validated by biotin pulldown. AUF-1-targets' steady-state levels were equally affected by partial or near-total AUF-1 loss induced by cytomix (TNF &amp; alpha;/IL1 &amp; beta;/IFN &amp; gamma;/10 nM each) and siRNA, respectively, with differential transcript decay rates. Cytomix-mediated decrease in AUF-1 levels in BEAS-2B and primary human small-airways epithelium (HSAEC) was replicated by treatment with the senescence- inducer compound etoposide and associated with readouts of cell-cycle arrest, increase in lysosomal damage and senescence-associated secretory phenotype (SASP) factors, and with AUF-1 transfer in extracellular vesicles, detected by transmission electron microscopy and immunoblotting. Extensive in-silico and genome ontology analysis found, consistent with AUF-1 functions, enriched RIP-Seq-derived AUF-1-targets in COPD-related pathways involved in inflammation, senescence, gene regulation and also in the public SASP proteome atlas; AUF-1 target signature was also significantly represented in multiple transcriptomic COPD databases generated from primary HSAEC, from lung tissue and from single-cell RNA-sequencing, displaying a predominant downregulation of expression. DiscussionLoss of intracellular AUF-1 may alter posttranscriptional regulation of targets particularly relevant for protection of genomic integrity and gene regulation, thus concurring to airway epithelial inflammatory responses related to oxidative stress and accelerated aging. Exosomal-associated AUF-1 may in turn preserve bound RNA targets and sustain their function, participating to spreading of inflammation and senescence to neighbouring cells
    • …
    corecore