Prediction of long-term hospitalisation and all-cause mortality in patients with chronic heart failure on Dutch claims data: a machine learning approach.

Background: Accurately predicting which patients with chronic heart failure (CHF) are particularly vulnerable for adverse outcomes is of crucial importance to support clinical decision making. The goal of the current study was to examine the predictive value on long term heart failure (HF) hospitalisation and all-cause mortality in CHF patients, by exploring and exploiting machine learning (ML) and traditional statistical techniques on a Dutch health insurance claims database.

Methods: Our study population consisted of 25,776 patients with a CHF diagnosis code between 2012 and 2014 and one year and three years follow-up HF hospitalisation (1446 and 3220 patients respectively) and all-cause mortality (2434 and 7882 patients respectively) were measured from 2015 to 2018.

Theory-driven classification of reading difficulties from fMRI data using Bayesian latent-mixture models.

Decades of research have led to several competing theories regarding the neural contributors to impaired reading. But how can we know which theory (or theories) identifies the types of markers that indeed differentiate between individuals with reading disabilities (RD) and their typically developing (TD) peers? To answer this question, we propose a new analytical tool for theory evaluation and comparison, grounded in the Bayesian latent-mixture modeling framework. We start by constructing a series of latent-mixture classification models, each reflecting one existing theoretical claim regarding the neurofunctional markers of RD (highlighting network-level differences in either mean activation, inter-subject heterogeneity, inter-region variability, or connectivity).

Increased Response to Altered Auditory Feedback in Dyslexia: A Weaker Sensorimotor Magnet Implied in the Phonological Deficit.

Purpose: The purpose of this study was to examine whether developmental dyslexia (DD) is characterized by deficiencies in speech sensory and motor feedforward and feedback mechanisms, which are involved in the modulation of phonological representations.

Method: A total of 42 adult native speakers of Dutch (22 adults with DD; 20 participants who were typically reading controls) were asked to produce /bep/ while the first formant (F1) of the /e/ was not altered (baseline), increased (ramp), held at maximal perturbation (hold), and not altered again (after-effect). The F1 of the produced utterance was measured for each trial and used for statistical analyses.