Hemodynamic cortical ripples through cyclicity analysis.

A fine-grained understanding of dynamics in cortical networks is crucial to unpacking brain function. Resting-state functional magnetic resonance imaging (fMRI) gives rise to time series recordings of the activity of different brain regions, which are aperiodic and lack a base frequency. Cyclicity analysis, a novel technique robust under time reparametrizations, is effective in recovering the temporal ordering of such time series, collectively considered components of a multidimensional trajectory.

A review of the association between in vitro fertilization and children's neurocognitive development.

This review investigated the current research on the association between in vitro fertilization and children's neurocognitive development. Twenty studies were analyzed, encompassing over 23,000 children conceived through IVF, and compared to those conceived naturally. The findings on overall cognitive function were mixed, as measured by IQ.

Machine learning in predicting heart failure survival: a review of current models and future prospects.

Heart failure is a complex and prevalent condition with significant implications for patient management and survival prediction. Traditional predictive models often fall short in accuracy due to their reliance on pre-specified predictors and assumptions of variable independence. This review aims to assess the role of machine learning (ML) algorithms in predicting heart failure survival, comparing their performance with traditional statistical methods and identifying key predictive features.