Latest AI and machine learning research in head trauma for healthcare professionals.
Trust and ethical concerns due to the widespread deployment of opaque machine learning (ML) models m...
Trust and ethical concerns due to the widespread deployment of opaque machine learning (ML) models m...
Machine unlearning is rapidly becoming a practical requirement, driven by privacy regulations, data ...
Purpose/Objective: Brain tumors result in 20 years of lost life on average. Standard therapies induc...
Segmentation is crucial for brain gliomas as it delineates the glioma s extent and location, aiding ...
Background Generative artificial intelligence (GenAI) in healthcare may reduce administrative burden...
Objective: Superresolution ultrasound (SR US) reveals microvascular structures with exquisite resolu...
Federated learning (FL) in post-deployment settings must adapt to non-stationary data streams across...
We present Neural Image-Space Tessellation (NIST), a lightweight screen-space post-processing approa...
Pre-trained generative models for residential floor plans are typically optimized to fit large-scale...
Machine learning (ML) models are effective at classifying images across various fields, including bi...
Scientific discovery pipelines typically involve complex, rigid, and time-consuming processes, from ...
Perinatal depression (PD) is common and disabling, yet its longitudinal comorbidity patterns and pre...
Objective: Post-thrombotic syndrome (PTS), a common complication of deep vein thrombosis, lacks obje...
Opportunities for medical students to gain practical experience in vaginal births are increasingly c...
Sepsis is a major public health concern due to its high morbidity, mortality, and cost. Its clinical...
Background: Post-operative tachycardia is a common and poorly understood complication following the ...
Spatial and activity-dependent gene regulation in the mammalian brain requires coordinated control o...
Current generative video models excel at producing novel content from text and image prompts, but le...
The concept of embodied sensorimotor decision-making proposes that processes implicated in evaluatin...
Weakly Supervised Semantic Segmentation (WSSS), which relies only on image-level labels, has attract...