Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 60,721 to 60,730 of 228,072 articles

When Are Two Scores Better Than One? Investigating Ensembles of Diffusion Models

arXiv
Diffusion models now generate high-quality, diverse samples, with an increasing focus on more powerful models. Although ensembling is a well-known way to improve supervised models, its application to unconditional score-based diffusion models remains... read more 

PubMed-OCR: PMC Open Access OCR Annotations

arXiv
PubMed-OCR is an OCR-centric corpus of scientific articles derived from PubMed Central Open Access PDFs. Each page image is annotated with Google Cloud Vision and released in a compact JSON schema with word-, line-, and paragraph-level bounding boxes... read more 

Sociotechnical Challenges of Machine Learning in Healthcare and Social Welfare

arXiv
Sociotechnical challenges of machine learning in healthcare and social welfare are mismatches between how a machine learning tool functions and the structure of care practices. While prior research has documented many such issues, existing accounts o... read more 

Topology-Guaranteed Image Segmentation: Enforcing Connectivity, Genus, and Width Constraints

arXiv
Existing research highlights the crucial role of topological priors in image segmentation, particularly in preserving essential structures such as connectivity and genus. Accurately capturing these topological features often requires incorporating wi... read more 

Anisotropic Tensor Deconvolution of Hyperspectral Images

arXiv
Hyperspectral image (HSI) deconvolution is a challenging ill-posed inverse problem, made difficult by the data's high dimensionality.We propose a parameter-parsimonious framework based on a low-rank Canonical Polyadic Decomposition (CPD) of the entir... read more 

Wetland mapping from sparse annotations with satellite image time series and temporal-aware segment anything model

arXiv
Accurate wetland mapping is essential for ecosystem monitoring, yet dense pixel-level annotation is prohibitively expensive and practical applications usually rely on sparse point labels, under which existing deep learning models perform poorly, whil... read more 

Latent Space Inference via Paired Autoencoders

arXiv
This work describes a novel data-driven latent space inference framework built on paired autoencoders to handle observational inconsistencies when solving inverse problems. Our approach uses two autoencoders, one for the parameter space and one for t... read more 

Heterogeneous Uncertainty-Guided Composed Image Retrieval with Fine-Grained Probabilistic Learning

arXiv
Composed Image Retrieval (CIR) enables image search by combining a reference image with modification text. Intrinsic noise in CIR triplets incurs intrinsic uncertainty and threatens the model's robustness. Probabilistic learning approaches have shown... read more 

Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype

arXiv
Glioblastoma, IDH-wildtype (GBM-IDHwt) is the most common malignant brain tumor. Histomorphology is a crucial component of the integrated diagnosis of GBM-IDHwt. Artificial intelligence (AI) methods have shown promise to extract additional prognostic... read more 

Beer-Lambert Autoencoder for Unsupervised Stain Representation Learning and Deconvolution in Multi-immunohistochemical Brightfield Histology Images

arXiv
Separating the contributions of individual chromogenic stains in RGB histology whole slide images (WSIs) is essential for stain normalization, quantitative assessment of marker expression, and cell-level readouts in immunohistochemistry (IHC). Classi... read more