Latest AI and machine learning research in pneumonia for healthcare professionals.
Community health workers (CHWs) in low-resource settings deliver variable-quality care. This study used OpenAI's o3 and Google's Gemini Flash 2.5 to evaluate whether large language models (LLMs) 'listening' to CHW-patient interactions could generate accurate referral decisions. Across 150 participating Rwandan CHWs, 429 encounters were recorded (in Kinyarwanda) and then processed by LLMs. CHWs dem...
Radiology Report Generation (RRG) through Vision-Language Models (VLMs) promises to reduce documentation burden, improve reporting consistency, and accelerate clinical workflows. However, their clinical adoption remains limited by the lack of interpretability and the tendency to hallucinate findings misaligned with imaging evidence. Existing research typically treats interpretability and accuracy ...
In critical decision support systems based on medical imaging, the reliability of AI-assisted decision-making is as relevant as predictive accuracy. A...
Bacterial infections are a major cause of morbidity and mortality among children under five in low- and middle-income countries (LMICs). Children in L...
Motivation: Gene regulatory networks provide fundamental insights into plant biology, yet extracting structured interaction data from scientific liter...
Deep neural networks for chest X-ray classification achieve strong average performance, yet often underperform for specific demographic subgroups, rai...
Proteins are dynamic molecular machines whose functions are determined by their structures. While static structures can offer initial insights or hypo...
Training a neural network requires navigating a high-dimensional, non-convex loss surface to find parameters that minimize this loss. In many ways, it...
The emergence of Janus kinase (JAK) inhibitors, a relatively new class of medications for autoimmune and inflammatory conditions, has been accompanied...
Background Foundation models have emerged as a promising paradigm for medical imaging AI [7], with claims of improved generalization and reduced bias....
Differential privacy (DP) provides formal protection for sensitive data but typically incurs substantial losses in diagnostic performance. Model initi...
In biomedical engineering, artificial intelligence has become a pivotal tool for enhancing medical diagnostics, particularly in medical image classifi...
Introduction: To improve upon the World Health Organization (WHO) 8 danger signs used to identify young infants (<2 months) requiring referral during ...
Difficulty replicating baselines, high computational costs, and required domain expertise create persistent barriers to clinical AI research. To addre...
Frontier models have demonstrated remarkable capabilities in understanding and reasoning with natural-language text, but they still exhibit major comp...
Artificial intelligence systems for chest radiograph interpretation are increasingly deployed in clinical practice, yet current fairness frameworks em...
The recent surge in popularity of Nano-Banana and Seedream 4.0 underscores the community's strong interest in multi-image composition tasks. Compared ...
We introduce MATEX (Multi-scale Attention and Text-guided Explainability), a novel framework that advances interpretability in medical vision-language...
Despite recent progress, medical foundation models still struggle to unify visual understanding and generation, as these tasks have inherently conflic...
With advancements in deep learning (DL) and computer vision techniques, the field of chart understanding is evolving rapidly. In particular, multimoda...