Latest AI and machine learning research in pneumonia for healthcare professionals.
Identifiable causal representation learning seeks to uncover the true causal relationships underlying a data generation process. In medical imaging, this presents opportunities to improve the generalisability and robustness of task-specific latent features. This work introduces the concept of grouping observations to learn identifiable representations for disease classification in chest X-rays v...
Phages, as obligate bacterial and archaeal parasites, constitute a virus group of paramount ecological significance due to their exceptional abundance and genetic diversity. These biological entities serve as critical regulators in Earth's ecosystems, driving biogeochemical cycles, energy fluxes, and ecosystem services across terrestrial and marine environments. Within soil microbiomes, phages fun...
Medical report generation from imaging data remains a challenging task in clinical practice. While large language models (LLMs) show great promise i...
In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or comp...
Counterfactual image generation aims to simulate realistic visual outcomes under specific causal interventions. Diffusion models have recently emerg...
Chest X ray (CXR) imaging remains a critical diagnostic tool for thoracic conditions, but current automated systems face limitations in pathology co...
Overlapping object perception aims to decouple the randomly overlapping foreground-background features, extracting foreground features while suppres...
While multimodal AI systems (models jointly trained on heterogeneous data types such as text, time series, graphs, and images) have become ubiquitou...
Chest radiography is widely used in diagnostic imaging. However, perceptual errors -- especially overlooked but visible abnormalities -- remain comm...
Knowledge graphs (KGs) are useful for analyzing social structures, community dynamics, institutional memberships, and other complex relationships ac...
In the past, the development of vaccines and immunotherapeutics relied heavily on trial-and-error experimentation and extensive in vivo testing, oft...
In celebration of Clinical Trials Day, May 20, this collection of Voices highlights visionary perspectives on the evolving landscape of clinical resea...
Claims made by individuals or entities are oftentimes nuanced and cannot be clearly labeled as entirely "true" or "false" -- as is frequently the ca...
Latent Diffusion Models have shown remarkable results in text-guided image synthesis in recent years. In the domain of natural (RGB) images, recent ...
The CXR-LT series is a community-driven initiative designed to enhance lung disease classification using chest X-rays (CXR). It tackles challenges i...
Lung cancer remains one of the most prevalent and fatal diseases worldwide, demanding accurate and timely diagnosis and treatment. Recent advancemen...
COVID-19 is a rapidly spreading and highly infectious virus which has triggered a global pandemic, profoundly affecting millions across the world. T...
As automated attack techniques rapidly advance, CAPTCHAs remain a critical defense mechanism against malicious bots. However, existing CAPTCHA schem...
The commercial vitality of community-scale streets in Chinese cities is shaped by complex interactions between vehicular accessibility, environmenta...
Purpose: This study proposes a framework for fine-tuning large language models (LLMs) with differential privacy (DP) to perform multi-abnormality cl...