AIMC Topic: Semantics

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Towards semantic-driven high-content image analysis: an operational instantiation for mitosis detection in digital histopathology.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
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 ...

Literature-based biomedical image classification and retrieval.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
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...

Toward a view-oriented approach for aligning RDF-based biomedical repositories.

Methods of information in medicine
INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems".

Semantic discrete decoder based on adaptive pixel clustering for monocular depth estimation.

Neural networks : the official journal of the International Neural Network Society
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...

Knowledge graph information bottleneck enhanced molecular representation learning.

Neural networks : the official journal of the International Neural Network Society
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...

Semantic-Rearrangement-based Hierarchical Alignment for domain generalized segmentation.

Neural networks : the official journal of the International Neural Network Society
Domain generalized semantic segmentation is an essential computer vision task, for which models only leverage source data to learn semantic segmentation towards generalizing to the unseen target domains. Previous works typically address this challeng...

Semantic Convergence with LLMs for Head and Neck Cancer Quality Indicators.

Studies in health technology and informatics
We developed a novel method for leveraging large language models (LLM) to systematically filter and categorize large numbers of clinical quality indicators (CQI) for head and neck cancer. This was used to transform a tedious, human-resource intensive...

Improving Radiology Report Generation with Semantic Understanding.

Studies in health technology and informatics
This study proposes RRG-LLM, a model designed to enhance RRG by effectively learning medical domain with minimal computational resources. Initially, LLM is finetuned by LoRA, enabling efficient adaptation to the medical domain. Subsequently, only the...

Multimodal Fusion of EHR in Structures and Semantics: Integrating Clinical Records and Notes with Hypergraph and LLM.

Studies in health technology and informatics
In recent decades, Electronic Health Records (EHRs) have become increasingly useful to support clinical decision-making and healthcare. EHRs usually contain heterogeneous information, such as structural data in tabular form and un-structured data in ...

Empirical Antonym Implementation in the UMLS SPECIALIST Lexicon.

Studies in health technology and informatics
Antonyms are words that have opposite or contrasting meanings in a specific domain. For example, "increase" is the opposite of "decrease" in the domain of "quantity". Antonyms play an important role in NLP applications to improve performance. This pa...