Latest AI and machine learning research in work force for healthcare professionals.
The rising prevalence of chronic wounds, especially in aging populations, presents a significant healthcare challenge due to prolonged hospitalizations, elevated costs, and reduced patient quality of life. Traditional wound care is resource-intensive, requiring frequent in-person visits that strain both patients and healthcare professionals (HCPs). Therefore, we present WoundAIssist, a patient-c...
Recent advances in text-to-image (T2I) models have achieved impressive quality and consistency. However, this has come at the cost of representation diversity. While automatic evaluation methods exist for benchmarking model diversity, they either require reference image datasets or lack specificity about the kind of diversity measured, limiting their adaptability and interpretability. To address...
Existing studies of innovation emphasize the power of social structures to shape innovation capacity. Emerging machine learning approaches, however,...
With the rapid advancement of generative models, the realism of AI-generated images has significantly improved, posing critical challenges for verif...
Large Language Models (LLMs) have demonstrated substantial efficacy in advancing graph-structured data analysis. Prevailing LLM-based graph methods ...
Computed tomography (CT) is a major medical imaging modality. Clinical CT scenarios, such as low-dose screening, sparse-view scanning, and metal imp...
Recently, Generative Adversarial Networks (GANs) have been successfully scaled to billion-scale large text-to-image datasets. However, training such...
The recent progress of large language model agents has opened new possibilities for automating tasks through graphical user interfaces (GUIs), espec...
Data heterogeneity plays a pivotal role in determining the performance of machine learning (ML) systems. Traditional algorithms, which are typically...
The expanding domain of digital mental health is transitioning beyond traditional telehealth to incorporate smartphone apps, virtual reality, and gene...
As dynamic interfaces governing molecular recognition and signal transduction, interactions between plants and microbes fundamentally shape ecosystem ...
The shear wave elastography (SWE) provides quantitative markers for tissue characterization by measuring the shear wave speed (SWS), which reflects ti...
Understanding the distribution of plant species diversity(PSD) along spatial and environmental gradients is essential for implementing effective conse...
OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottles. Rates of blood stream infection (BSI) among cr...
Although still limited, the integration of artificial intelligence (AI) in health care has rapidly expanded in the past few years, especially in oncol...
In many medical and pharmaceutical processes, continuous hygiene monitoring is crucial, often involving the manual detection of microorganisms in agar...
It may only be a handful of years before fully autonomous neurosurgical robots (ANRs) are pushed into widespread clinical adoption. Nevertheless, whet...
With the advancement of modern medicine and the development of technologies such as MRI, CT, and cellular analysis, it has become increasingly criti...
Current self-correction approaches in text-to-SQL face two critical limitations: 1) Conventional self-correction methods rely on recursive self-call...
Tumor data synthesis offers a promising solution to the shortage of annotated medical datasets. However, current approaches either limit tumor diver...