Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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Development and external validation of deep learning models for spontaneous preterm birth prediction from mid-trimester cervical ultrasound

Preterm birth is the leading cause of neonatal death. Despite sustained efforts to identify high-risk women in the mid-trimester, accurate prediction remains difficult. Quantitative cervical ultrasound texture has been proposed as a predictor of spontaneous preterm birth. However, earlier models were developed in small single-centre samples and were not externally validated. We developed image-tex...

Predicting phenotypes with one step genetic decision trees

Genomic prediction of complex traits is limited when phenotype records are restricted and when using linear models. Increasing the amount of phenotypic data with high-throughput, image-based phenotyping could result in better genomic prediction and stronger signals in variant detection. Here, we analysed phenotypic and genomic data from a selectively bred cohort of the Australasian snapper (Chryso...

Spatial machine learning and longitudinal analysis of skilled antenatal care access and fertility-related inequities in Ghana (1988-2022)

This study focuses on the relationship between access to Advanced Neonatal Care (ANC) and fertility across the regions in Ghana between 1988 and 2022....

Knowledge-Guided Cross-Modal Fusion for Adult-to-Pediatric ECG Transfer via Label-Conditioned Contrastive Alignment

Adult and pediatric electrocardiogram (ECG) interpretation relies on age-sensitive criteria, and models pretrained mainly on adult ECGs often transfer...

Jul 17 2026 2607.15928v1
Spatio-temporal 3D Mapping of Mouse Cerebellar Vascularization during Embryonic Development

Despite major advances in the study of cerebellar neurogenesis, cerebellar angiogenesis during embryogenesis remains poorly described. Recent advances...

Deep Learning Approaches for Sleep Apnea Classification from Polysomnographic EEG Signals

Sleep apnea diagnosis via polysomnography remains resource intensive and relies on time consuming manual data analysis and scoring. Recent work has de...

Jul 16 2026 2607.15477v1
Multi-matrix copper exposure is associated with reduced olfactory bulb volume and odor sensitivity in adolescents

Copper (Cu) is an essential metal involved in neurobiological processes including energy metabolism and neurotransmission, yet dysregulated Cu levels ...

Multimodal Semantic-Aware Contrastive Learning For False Negative Mitigation in 3D Medical Imaging

Multimodal Contrastive Learning (CL) has shown significant performance in aligning representations across various data modalities and improving downst...

Jul 16 2026 2607.14995v1
Neuroanatomical Subtypes of Callous-Unemotional Traits in a Community Sample of Youth

Importance. Callous Unemotional (CU) traits are associated with significant clinical and neurophysiological heterogeneity that may affect treatment ef...

TEDDY: A Pediatric Foundation Model for Risk Forewarning from ICD-Coded Diagnostic Histories

Pediatric electronic health records capture developmentally structured clinical trajectories, yet their potential for generative healthcare foundation...

Jul 15 2026 2607.14191v1
The Swiss Integrated Care (INCA) Study: Description of a Novel Prospective Cohort of Patients and Caregivers in Reimbursed Informal Care

Methods INCA is a prospective, single-center cohort study with nationwide recruitment. Participation is open to adult patients and informal caregivers...

The topology of adolescent mental health

The increased vulnerability to mental health problems in adolescence is frequently reported but poorly understood, hampered by a rigid diagnostic syst...

Life-Stage Heterogeneity in the Mental Health Treatment Gap: An Unsupervised Machine Learning Profiling of Symptomatic US Adults

Abstract Background Despite a rising global psychiatric burden, a treatment gap persists where the majority of symptomatic individuals remain unmedica...

Introducing PHJ Media: A Unique Machine Learning -Driven Basal Formulation to Overcome Recalcitrance for Multi-Genotype Micropropagation of Cannabis sativa L.

Applications of tissue culture are critical for Cannabis sativa L. (cannabis), supporting clonal propagation, germplasm preservation, pathogen elimina...

AnomExpert: Identifying and Selecting Anatomical Planes for Prenatal Ultrasound Anomaly Diagnosis

Life-limiting congenital anomalies require accurate prenatal diagnosis for appropriate clinical decision-making. Prenatal ultrasound (US) examinations...

Jul 15 2026 2607.13409v1
From Current-Wave to Longitudinal Risk Prediction: A Leakage-Aware Stacked Ensemble Framework for Adolescent Substance Use Using the ABCD Study

Adolescent use of alcohol, nicotine, and marijuana remains a major public health concern in the United States. Early identification of youth at elevat...

FlowPET: Physics-Informed Symplectic Flow Matching for Low-Count PET Reconstruction

Low-count Positron Emission Tomography (PET) reconstruction is severely hindered by the dissipative nature of prevailing generative models, where the ...

Jul 13 2026 2607.11104v1
Neonatal Seizure Detection Using Combined aEEG and Compressed Spectral Array Features: A Machine-Learning Proof-of-Concept Study

Background To build a clinically translatable neonatal seizure detection algorithm using amplitude-integrated electroencephalography (aEEG) and compre...

Alignment-Free RoPE-Based Dual-Stream Transformer for PPG-Guided Neonatal ECG Segment Inpainting in the NICU

Adhesive electrocardiography (ECG) electrodes used in neonatal intensive care units (NICUs) may cause skin injury in premature infants. Although photo...

Uncertainty-aware extraction of clinical findings from Finnish EHRs using open large language models

Objective. To evaluate whether open-weight large language models (LLMs) can accurately extract clinical findings from Finnish-language pediatric recor...

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