SUMMARY: Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computati...
Biologists often need to know the set S' of genes that are the most functionally and semantically related to a given set S of genes. For determining the set S', most current gene similarity measures overlook the structural dependencies among the Gene...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Oct 2, 2014
This study concerns a novel symbolic cognitive vision framework emerged from the Cognitive Microscopy (MICO(1)) initiative. MICO aims at supporting the evolution towards digital pathology, by studying cognitive clinical-compliant protocols involving ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 20, 2014
Literature-based image informatics techniques are essential for managing the rapidly increasing volume of information in the biomedical domain. Compound figure separation, modality classification, and image retrieval are three related tasks useful fo...
INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems".
IEEE transactions on visualization and computer graphics
Oct 1, 2025
Large language models (LLMs) have gained widespread popularity due to their ability to perform ad-hoc natural language processing (NLP) tasks with simple natural language prompts. Part of the appeal for LLMs is their approachability to the general pu...
Studies in health technology and informatics
Sep 3, 2025
INTRODUCTION: Manual ICD-10 coding of German clinical texts is time-consuming and error-prone. This project aims to develop a semi-automated pipeline for efficient coding of unstructured medical documentation.
Deep learning-based semantic segmentation approaches provide an efficient and automated means for cancer diagnosis and monitoring, which is important in clinical applications. However, implementing these approaches outside the experimental environmen...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Monocular depth estimation (MDE) has long been a popular and challenging task. Currently, mainstream methods mainly include regression methods based on geometric constraints and ordinal regression methods based on discretized depth intervals. However...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Effective molecular representation learning (MRL) is essential for advancing molecular property prediction. In recent years, graph-based MRL methods have made significant progress by effectively utilizing the topology structure of molecules. Research...
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