Latest AI and machine learning research in pediatrics for healthcare professionals.
In current medical practice, patients undergoing depression treatment must wait four to six weeks before a clinician can assess medication response due to the delayed noticeable effects of antidepressants. Identification of a treatment response at any earlier stage is of great importance, since it can reduce the emotional and economic burden connected with the treatment. We approach the predicti...
By use of complex network dynamics and graph-based machine learning, we identified critical determinants of lineage-specific plasticity across the single-cell transcriptomics of pediatric high-grade glioma (pHGGs) subtypes: IDHWT glioblastoma and K27M-mutant glioma. Our study identified network interactions regulating glioma morphogenesis via the tumor-immune microenvironment, including neurodev...
Automated viewpoint classification in echocardiograms can help under-resourced clinics and hospitals in providing faster diagnosis and screening whe...
Visual Question Answering (VQA) is an evolving research field aimed at enabling machines to answer questions about visual content by integrating ima...
Tracking and acquiring simultaneous optical images of randomly moving targets obscured by scattering media remains a challenging problem of importan...
This report, authored in 2003, presents an innovative approach to the management and utilization of audiovisual archives in the humanities and socia...
Fungi undergo dynamic morphological transformations throughout their lifecycle, forming intricate networks as they transition from spores to mature ...
Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on...
BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, whi...
Clinical assessments for neuromuscular disorders, such as Spinal Muscular Atrophy (SMA) and Duchenne Muscular Dystrophy (DMD), continue to rely on s...
Since the beginning of rephotography in the middle of the 19th century, techniques in registration, conservation, presentation, and sharing of repho...
Non-invasive, efficient, physical token-less, accurate and stable identification methods for newborns may prevent baby swapping at birth, limit baby...
The introduction of optical coherence tomography (OCT) in the 1990s revolutionized diagnostic ophthalmic imaging. Initially, OCT's role was primarily ...
Understanding how the brain represents sensory information and triggers behavioural responses is a fundamental goal in neuroscience. Recent advances i...
Adolescent major depressive disorder (MDD) is characterized by heterogeneous symptomatology and complex neurodevelopmental underpinnings. Here, we inv...
Model-informed precision dosing (MIPD) utilizes pharmacokinetic/pharmacodynamic (PK/PD) models to optimize drug therapy. However, conventional MIPD of...
The application of transfer learning models to large scale single-cell datasets has enabled the development of single-cell foundation models (scFMs) t...
Pathogenic KCNQ2 variants are associated with developmental and epileptic encephalopathy (KCNQ2-DEE), a devastating disorder characterized by neonatal...
Cancer subtype classification is critical for precision therapy and there is a growing trend of augmenting histopathology testing procedures with omic...
Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises ...