Albertlaursen9886

We conduct experiments on 4 medical image segmentation datasets, and experiment results show that the proposed MSDN model outperforms multiple baselines.The incorporation of a-priori knowledge on the shape of anatomical structures and their variation through Statistical Shape Models (SSMs) has shown to be very effective in guiding highly uncertain image segmentation problems. In this paper, we construct multiple-structure SSMs of purely geometric nature, that describe the relationship between adjacent anatomical components through Canonical Correlation Analysis. Shape inference is then conducted based on a regularization term on the shape likelihood providing more reliable structure representations. A fundamental prerequisite for performing statistical shape analysis on a set of objects is the identification of corresponding points on their associated surfaces. We address the correspondence problem using the recently proposed Functional Maps framework, which is a generalization of point-to-point correspondence to manifolds. Additionally, we show that, by incorporating techniques from the deep learning theory into this framework, we can further enhance the ability of SSMs to better capture the shape variation in a given dataset. The efficiency of our approach is illustrated through the creation of 3D models of the human knee complex in two application scenarios incomplete or noisy shape reconstruction and missing structure estimation.

Early onset of alcohol use is associated with an increased risk of substance use disorders (SUD), but few studies have examined associations with other psychiatric disorders. Our aim was to study the association between the age of first alcohol intoxication (AFI) and the risk of psychiatric disorders in a Finnish general population sample.

We utilized a prospective, general population-based study, the Northern Finland Birth Cohort 1986. In all, 6,290 15-16-year old adolescents answered questions on AFI and were followed up until the age of 33years for psychiatric disorders (any psychiatric disorder, psychosis, SUD, mood disorders and anxiety disorders) by using nationwide register linkage data. Cox-regression analysis with Hazard Ratios (HR, with 95% confidence intervals (CI)) was used to assess the risk of psychiatric disorders associated with AFI.

Statistically significant associations were observed between AFI and any psychiatric disorder, psychosis, SUDs, and mood disorders. After adjustments for otne the first instances of adolescent alcohol intoxication.

This study aimed to document changes in puffing topography and, the effects of device type and nicotine concentration on puffing topography, subjective effects and smoking behaviour over two weeks of e-cigarette (EC) use.

EC naïve smokers (N=50; 64% female) were randomly allocated to a cigalike (18mg/mL) or tank containing either 18 (Tank18) or 6mg/mL nicotine concentrations (Tank6). AT7519 In 3 separate sessions (Baseline, 1 and 2weeks post-baseline), participants vaped 20min ad-libitum. Puff duration, puff number, inter-puff intervals (IPI), exhaled carbon monoxide (CO), cigarettes per day (CPD), cigarette dependence, craving, withdrawal, and subjective effects were recorded.

Two weeks post-baseline, puff duration and IPI significantly increased whilst puff number decreased. Cigalikes were associated with greater puff number and shorter IPI compared to Tanks; there was no difference between Tank18 and Tank6. CPD, CO and cigarette dependence reduced significantly from baseline to week1 but did not differ betw.

Unplanned drinking, or drinking that violates intentions, has been linked to significant alcohol-related consequences; however, little is known about what factors within individuals' daily lives predict whether unplanned drinking occurs. This study examines the influence of daily-life impulsivity, alcohol craving, and interpersonal contexts on unplanned drinking.

Ecological Momentary Assessment (EMA) data were collected from 32 moderate drinkers. Participants were prompted six times per day for up to 21days. Each morning participants reported whether they planned to drink that day. Multilevel and GEE models predicted drinking behaviors on days without intent to drink from daily-life interpersonal contexts, and pre-drinking ratings of impulsivity and craving.

Spending time in a bar and spending relatively more time with other people on days with no intention to drink was associated with drinking. Individuals who experienced higher craving prior to drinking were relatively more likely to engage in unplanned drinking. When participants reported relatively greater difficulties with premeditation, they were more likely to subsequently report initiating an unplanned drinking episode. Results also suggest that individuals generally higher on negative urgency may be less likely to engage in unplanned drinking but drink more when they do.

These results indicate the influence of daily-life contexts, craving, and impulsivity on unplanned drinking behavior. We highlight several possible avenues for intervention and prevention efforts including modifying social and interpersonal environments, screening for craving patterns, and targeting cognitive deficits in planning.

These results indicate the influence of daily-life contexts, craving, and impulsivity on unplanned drinking behavior. We highlight several possible avenues for intervention and prevention efforts including modifying social and interpersonal environments, screening for craving patterns, and targeting cognitive deficits in planning.

Dual-process models of substance use (Wiers et al., 2007) propose that whether automatic processes (i.e., implicit attitudes) influence use depends on self-regulation, such that an individual is more likely to act in accordance with automatically activated implicit attitudes when there is limited capacity for self-regulation (a two-way interaction). In this model, the relevance of self-regulation likely depends on whether an individual recognizes reasons or the need to inhibit substance use. The current study tested a three-way interaction between implicit cannabis attitudes, self-regulation, and negative expectancies to prospectively predict adolescent cannabis use.

A community sample of late adolescents (N=246; M age=19.02) were assessed across two annual time points. Negative binomial regressions predicting adolescent cannabis use were estimated to test the proposed interaction using two indictors of self-regulation (effortful control and working memory) above and beyond prior cannabis use and demographic covariates.