Latest AI and machine learning research in adhd/add for healthcare professionals.
We consider a multistatic radio-frequency imaging problem with anisotropy, in which the reflection from a point depends on the positions of the transmit (Tx) and receive (Rx) arrays. The goal is to label the voxels of a field of view by a finite set of semantic classes and to group them into object instances. For the image formation of each Tx--Rx pair we apply a standard inverse-problem solver, a...
Unified multimodal models (UMMs) can perform both understanding and generation, raising a central question: can visual generation improve understanding? Existing evaluations provide mixed evidence, but confound task difficulty, reasoning paradigms, and the closed-loop interaction between generation and understanding. We introduce VGAU-Diag, a fine-grained evaluation framework for vision generation...
Co-registration underlies nearly every multi-temporal and multi-sensor use of optical satellite imagery, and operational products still carry document...
Reference-based diffusion stylization requires separating target geometry from transferable appearance. Existing tuning-based methods often rely on al...
The rat gambling task (rGT) has been widely used to investigate the neural mechanisms underlying risky choice and motor impulsivity. Here, rats sample...
General-purpose language models generate fluent health reports that can fabricate derived clinical metrics. In an illustrative comparison on identical...
Augmentation can corrupt a training example when an image and its annotations receive different random changes. A crop must use the same coordinates f...
Dementia affects more than 55 million people worldwide, and its progressive decline is difficult to track using infrequent in-person assessments, whic...
Fossil leaves are rarely preserved whole -- sedimentary rock hides, breaks, and erodes the lamina, yet paleobotany depends on the complete shape and o...
On-policy distillation (OPD) has become an effective approach for consolidating multiple task-specialized image generation models into a single studen...
Overlapped friction ridge patterns are a recurring problem in latent fingerprints recovered from crime scenes and in live-scan scenarios where residua...
Multimodal representation learning is a cornerstone of modern AI. By encoding multimodal queries and targets into vectors, it powers industrial search...
Prompt tuning adapts vision--language models with few trainable parameters, but existing approaches trade off efficiency and adaptation: static textua...
Fine-grained segmentation of auricular structures in CT is challenging because the ear occupies a small image region, cartilage boundaries are highly ...
Computer vision models have become highly effective for medical applications, yet their black-box nature continues to undermine clinician trust. In cl...
Electroencephalography (EEG) is widely used to diagnose neurological conditions, but its analysis usually relies on either predefined spectral feature...
The rapidly increasing number of video tracking-based behavioral summary tools and methods raises the question as to the most suitable approaches for ...
Automatic image colorization enables large-scale and low-cost reuse of grayscale media (e.g., manga panels and archival photographs), facilitating una...
Pediatric electronic health records capture developmentally structured clinical trajectories, yet their potential for generative healthcare foundation...
We propose Bi-PT, a pipeline for reconstructing 3D four-chamber human heart meshes from clinical sparsely sampled cardiac magnetic resonance imaging (...