Publications by authors named "J A Ricard"

The optimal modalities of kidney replacement therapy (KRT) in the ICU remain debated. Intermittent haemodialysis (IHD) and continuous veno-venous haemofiltration (CVVH) are the two main methods. Intermittent haemodialysis requires a water treatment system, which may not be available in all jurisdictions.

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Background: Exposure to community violence is associated with increased occurrence of substance use disorders (SUD). The self-medication hypothesis states that heightened negative emotionality may underlie the link between exposure to community violence and SUD. However, it is not well-understood if access to community resources, a broader public health approach, influences the purported psychological mechanisms underlying the link between community violence exposure and SUD.

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Considerable heterogeneity exists in the expression of complex human behaviors across the cognitive, personality and mental health domains. It is increasingly evident that individual variability in behavioral expression is substantially affected by sociodemographic factors that often interact with life experiences. Here, we formally address the urgent need to incorporate intersectional identities in neuroimaging studies of behavior, with a focus on research in mental health.

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Background And Aims: Estimating the genetic risk of coronary artery disease (CAD) is now possible by aggregating data from genome-wide association studies (GWAS) into polygenic risk scores (PRS). Combining multiple PRS for specific circulating blood lipids could improve risk prediction. Here, we sought to evaluate the performance of PRS derived from CAD and blood lipids GWAS to predict the incidence of CAD.

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Article Synopsis
  • The goal of computational psychiatry is to create models that connect differences in brain function to cognitive impairments and symptoms, which are often resistant to treatment.* -
  • Research shows that to predict cognitive functioning accurately, large participant samples are needed, highlighting limitations in smaller patient studies.* -
  • Using a transfer learning approach on neuroimaging data from the UK Biobank, the study found that predictions of cognitive functioning improved significantly, even with smaller sample sizes, validating the effectiveness of training models on larger datasets.*
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