Latest AI and machine learning research in pneumonia for healthcare professionals.
Accurate and early diagnosis of pneumonia through X-ray imaging is essential for effective treatment and improved patient outcomes. Recent advancements in machine learning have enabled automated diagnostic tools that assist radiologists in making more reliable and efficient decisions. In this work, we propose a Singular Value Decomposition-based Least Squares (SVD-LS) framework for multi-class p...
Recent advances in reasoning-enhanced large language models (LLMs) and multimodal LLMs (MLLMs) have significantly improved performance in complex tasks, yet medical AI models often overlook the structured reasoning processes inherent in clinical practice. In this work, we present ChestX-Reasoner, a radiology diagnosis MLLM designed to leverage process supervision mined directly from clinical rep...
Machine learning (ML) systems for medical imaging have demonstrated remarkable diagnostic capabilities, but their susceptibility to biases poses sig...
Data from domains such as social networks, healthcare, finance, and cybersecurity can be represented as graph-structured information. Given the sens...
Online community platforms require dynamic personalized retrieval and recommendation that can continuously adapt to evolving user interests and new ...
Many barriers exist when new members join a research community, including impostor syndrome. These barriers can be especially challenging for underg...
The continuous improvement in weather forecast skill over the past several decades is largely due to the increasing quantity of available satellite ...
Diagnostic imaging relies on interpreting both images and radiology reports, but the growing data volumes place significant pressure on medical expe...
The analysis of plant developmental plasticity, including root system architecture, is fundamental to understanding plant adaptability and developme...
Including children's images in datasets has raised ethical concerns, particularly regarding privacy, consent, data protection, and accountability. T...
Phytoplankton absorb and scatter light in unique ways, subtly altering the color of water, changes that are often minor for human eyes to detect but...
The application of artificial intelligence (AI) in medical imaging has revolutionized diagnostic practices, enabling advanced analysis and interpret...
This review synthesizes advances in predictive processing within the sensory cortex. Predictive processing theorizes that the brain continuously pre...
Reliable artificial intelligence (AI) models for medical image analysis often depend on large and diverse labeled datasets. Federated learning (FL) ...
This paper proposes a novel pooling-based VGG-Lite model in order to mitigate class imbalance issues in Chest X-Ray (CXR) datasets. Automatic Pneumo...
Automated radiology report generation (RRG) holds potential to reduce radiologists' workload, especially as recent advancements in large language mo...
In this retrospective study, a dataset was constructed with two parts. The first part included 1,656 synthetic chest radiology reports generated by ...
Accurate medical symptom coding from unstructured clinical text, such as vaccine safety reports, is a critical task with applications in pharmacovig...
Large vision-language models (LVMs) hold a great promise for automating medical report generation, potentially reducing the burden of manual reporti...
Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and...