State-of-the-art text-to-image diffusion models (DMs) achieve remarkable
quality, yet their massive parameter scale (8-11B) poses significant challenges
for inferences on resource-constrained devices. In this paper, we present
HierarchicalPrune, a ... read more
Journal of the American Society for Mass Spectrometry
Aug 6, 2025
Lung cancer metastasis, the leading cause of patient mortality, is driven by circulating tumor cells (CTCs), which act as direct mediators of metastatic spread. To elucidate the metabolic heterogeneity across lung cancer metastatic stages, a panorami... read more
Traditional diagnostic methods for asthma, a widespread chronic respiratory illness, are often limited by factors such as patient cooperation with spirometry. Non-invasive acoustic analysis using machine learning offers a promising alternative for ob... read more
Coarse room layout estimation provides important geometric cues for many
downstream tasks. Current state-of-the-art methods are predominantly based on
single views and often assume panoramic images. We introduce PixCuboid, an
optimization-based app... read more
Lung adenocarcinoma (LUAD), the most common non-small cell lung cancer subtype, often presents with subtle early symptoms leading to delayed diagnosis. Ferroptosis, a cell death process associated with iron metabolism dysregulation, has been linked t... read more
Cancer disparities in low- and middle-income countries (LMICs) persist because of socioeconomic inequalities and limited access to screening infrastructure, which requires equitable diagnostic solutions. As researchers, we need to develop interventio... read more
Optimizing clinical pathways is pivotal for enhancing healthcare delivery, yet traditional methods are increasingly insufficient in the face of complex, personalized medical demands. This paper introduces an innovative optimization framework that fus... read more
As deep learning-based, data-driven information extraction systems become
increasingly integrated into modern document processing workflows, one primary
concern is the risk of malicious leakage of sensitive private data from these
systems. While so... read more
Collecting real-world data for rare high-risk scenarios, long-tailed driving
events, and complex interactions remains challenging, leading to poor
performance of existing autonomous driving systems in these critical
situations. In this paper, we pr... read more
With the advancement of Artificial Intelligence (AI) towards multiple
modalities (language, vision, speech, etc.), multi-modal models have
increasingly been used across various applications (e.g., visual question
answering or image generation/capti... read more
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.