Latest AI and machine learning research in work force for healthcare professionals.
Data heterogeneity plays a pivotal role in determining the performance of machine learning (ML) sy...
The expanding domain of digital mental health is transitioning beyond traditional telehealth to inco...
The shear wave elastography (SWE) provides quantitative markers for tissue characterization by measu...
OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottl...
Although still limited, the integration of artificial intelligence (AI) in health care has rapidly e...
In many medical and pharmaceutical processes, continuous hygiene monitoring is crucial, often involv...
It may only be a handful of years before fully autonomous neurosurgical robots (ANRs) are pushed int...
With the advancement of modern medicine and the development of technologies such as MRI, CT, and c...
Current self-correction approaches in text-to-SQL face two critical limitations: 1) Conventional s...
Tumor data synthesis offers a promising solution to the shortage of annotated medical datasets. Ho...
The swift evolution of telehealth has revolutionized how medical professionals deliver healthcare ...
While pre-trained multimodal representations (e.g., CLIP) have shown impressive capabilities, they...
Recent advances in diffusion models have led to impressive image generation capabilities, but alig...
Perceptual voice quality assessment is essential for diagnosing and monitoring voice disorders by ...
Classifier-Free Guidance (CFG) is a widely used technique for improving conditional diffusion mode...
Temporal Logic (TL), especially Signal Temporal Logic (STL), enables precise formal specification,...
The quality of training data is critical to the performance of machine learning applications in do...
Recent advances in video generation models have sparked interest in world models capable of simula...
Natural images exhibit label diversity (clean vs. noisy) in noisy-labeled image classification and...
The substantial training cost of diffusion models hinders their deployment. Immiscible Diffusion r...
As learned image compression (LIC) methods become increasingly computationally demanding, enhancin...