相关论文: Neuro-imagerie n\'eonatale : quelle valeur pr\'edi…

Functional development of affective and reward circuits, cognition and response inhibition later in life exhibits vulnerability periods during gestation and early childhood. Extensive evidence supports the model that exposure to stressors…

Sensory prediction (SP) is a fundamental mechanism of perception that supports cognitive development. Atypical SP has been reported across multiple neurodevelopmental disorders (ND), suggesting it may constitute an early cross-syndromic…

Neuroimaging has profoundly enhanced our understanding of the human brain by characterizing its structure, function, and connectivity through modalities like MRI, fMRI, EEG, and PET. These technologies have enabled major breakthroughs…

A major challenge in medical image analysis is the automated detection of biomarkers from neuroimaging data. Traditional approaches, often based on image registration, are limited in capturing the high variability of cortical organisation…

Preterm birth is the most common cause of neonatal death. Current diagnostic methods that assess the risk of preterm birth involve the collection of maternal characteristics and transvaginal ultrasound imaging conducted in the first and…

Although most pregnancies result in a good outcome, complications are not uncommon and can be associated with serious implications for mothers and babies. Predictive modeling has the potential to improve outcomes through better…

Background: Being born very or extreme preterm is a major source of cerebral anomalies and neurodevelopmental disorders, whose occurrence depends on many perinatal factors. A better understanding of these factors could be provided by…

Preterm births occur at an alarming rate of 10-15%. Preemies have a higher risk of infant mortality, developmental retardation and long-term disabilities. Predicting preterm birth is difficult, even for the most experienced clinicians. The…

Exploring the developing brain is a major issue in understanding what enables children to acquire amazing abilities, and how early disruptions can lead to a wide range of neurodevelopmental disorders. MRI plays a key role here by providing…

Modifications of signaling pathways and synapses owing to changing behaviors, environments, numerous neural modulation as well as brain-tissue injuries is defined as neuroplasticity in developmental neurology. The central purpose of the…

We review evidence supporting the role of early life programming in the susceptibility for adult neurodegenerative diseases while highlighting questions and proposing avenues for future research to advance our understanding of this…

Normative modelling is an increasingly common statistical technique in neuroimaging that estimates population-level benchmarks in brain structure. It enables the quantification of individual deviations from expected distributions whilst…

Preterm infants with very low birth weight suffer from a high risk of intra-ventricular hemorrhage(IVH) and other serious diseases. To improve the clinical risk assessment of preterm infants and develop potential clinically makers for the…

Preterm infants (born between 28 and 37 weeks of gestation) face elevated risks of neurodevelopmental delays, making early identification crucial for timely intervention. While deep learning-based volumetric segmentation of brain MRI scans…

Most pregnancies and births result in a good outcome, but complications are not uncommon and when they do occur, they can be associated with serious implications for mothers and babies. Predictive modeling has the potential to improve…

Birth weight serves as a fundamental indicator of neonatal health, closely linked to both early medical interventions and long-term developmental risks. Traditional predictive models, often constrained by limited feature selection and…

Large-scale brain imaging datasets provide unprecedented opportunities for developing domain foundation models through pretraining. However, unlike natural image datasets in computer vision, these neuroimaging data often exhibit high…

Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, accurate automated systems to support clinical decision-making during delivery are currently…

For many neurological disorders, prediction of disease state is an important clinical aim. Neuroimaging provides detailed information about brain structure and function from which such predictions may be statistically derived. A multinomial…

Accurate fetal birth weight prediction is a cornerstone of prenatal care, yet traditional methods often rely on imaging technologies that remain inaccessible in resource-limited settings. This study presents a novel machine learning-based…