Latest AI and machine learning research in alternative medicine for healthcare professionals.
Echinacea is used for its immunostimulating properties and may have a role in modulating adverse imm...
Reactive oxygen and nitrogen species (RONS) are involved in deleterious/beneficial biological proces...
While Deep Neural Networks (DNNs) achieve remarkable performance, their tendency to produce overconf...
Image geo-localization aims to determine where a photograph was taken, a task that often requires mo...
Frontier multimodal large language models (MLLMs) have been reported to achieve over 90% accuracy on...
Benchmarks increasingly guide deployment, procurement and scientific screening, yet a score supports...
Clinical AI systems have achieved strong predictive performance; however, prediction accuracy is not...
Visual Question Answering (VQA) holds great promise for clinical support, particularly in ophthalmol...
Background: African Americans (AA) experience disproportionate burden of colorectal cancer (CRC). Dy...
Accurate risk stratification of pigmented skin lesions is critical for early melanoma detection and ...
Vision-Language Models (VLMs) excel at multimodal reasoning, yet it remains unclear whether their an...
Contrastively trained vision-language models such as CLIP provide strong zero-shot transfer by align...
Learned image compression (LIC) increasingly requires reconstructions that balance distortion fideli...
Monocular 3D object detection remains challenging because metric size and depth are underdetermined ...
Memory is essential for large vision-language models (LVLMs) to handle long, multimodal interactions...
Disease screening is critical for early detection and timely intervention in clinical practice. Howe...
Vision-Language Models (VLMs) increasingly operate on ultra-high-resolution (UHR) Earth observation ...
The opaque nature of deep learning models remains a significant barrier to their clinical adoption i...
End-to-end autonomous driving models generate future trajectories from multi-view inputs, improving ...
Medical multimodal large language models (MLLMs) have advanced image understanding and short-video a...
Large language models are increasingly deployed in clinical decision-support contexts, yet systemati...