AI Medical Compendium Topic

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Semantics

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BioGSF: a graph-driven semantic feature integration framework for biomedical relation extraction.

Briefings in bioinformatics
The automatic and accurate extraction of diverse biomedical relations from literature constitutes the core elements of medical knowledge graphs, which are indispensable for healthcare artificial intelligence. Currently, fine-tuning through stacking v...

EmoAtlas: An emotional network analyzer of texts that merges psychological lexicons, artificial intelligence, and network science.

Behavior research methods
We introduce EmoAtlas, a computational library/framework extracting emotions and syntactic/semantic word associations from texts. EmoAtlas combines interpretable artificial intelligence (AI) for syntactic parsing in 18 languages and psychologically v...

Supporting vision-language model few-shot inference with confounder-pruned knowledge prompt.

Neural networks : the official journal of the International Neural Network Society
Vision-language models are pre-trained by aligning image-text pairs in a common space to deal with open-set visual concepts. Recent works adopt fixed or learnable prompts, i.e., classification weights are synthesized from natural language description...

Multi-Label Zero-Shot Learning Via Contrastive Label-Based Attention.

International journal of neural systems
Multi-label zero-shot learning (ML-ZSL) strives to recognize all objects in an image, regardless of whether they are present in the training data. Recent methods incorporate an attention mechanism to locate labels in the image and generate class-spec...

DenseSeg: joint learning for semantic segmentation and landmark detection using dense image-to-shape representation.

International journal of computer assisted radiology and surgery
PURPOSE: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for se...

Semantic abnormalities in schizophrenia and bipolar disorder: A natural language processing approach.

Science progress
INTRODUCTION: The diagnostic boundaries between schizophrenia and bipolar disorder are controversial due to the ambiguity of psychiatric nosology. From this perspective, it is noteworthy that formal thought disorder has historically been considered p...

Graph anomaly detection based on hybrid node representation learning.

Neural networks : the official journal of the International Neural Network Society
Anomaly detection on graph data has garnered significant interest from both the academia and industry. In recent years, fueled by the rapid development of Graph Neural Networks (GNNs), various GNNs-based anomaly detection methods have been proposed a...

Semantic search helper: A tool based on the use of embeddings in multi-item questionnaires as a harmonization opportunity for merging large datasets - A feasibility study.

European psychiatry : the journal of the Association of European Psychiatrists
BACKGROUND: Recent advances in natural language processing (NLP), particularly in language processing methods, have opened new avenues in semantic data analysis. A promising application of NLP is data harmonization in questionnaire-based cohort studi...

A discrete convolutional network for entity relation extraction.

Neural networks : the official journal of the International Neural Network Society
Relation extraction independently verifies all entity pairs in a sentence to identify predefined relationships between named entities. Because these entity pairs share the same contextual features of a sentence, they lead to a complicated semantic st...

Enhancing semantical text understanding with fine-tuned large language models: A case study on Quora Question Pair duplicate identification.

PloS one
Semantical text understanding holds significant importance in natural language processing (NLP). Numerous datasets, such as Quora Question Pairs (QQP), have been devised for this purpose. In our previous study, we developed a Siamese Convolutional Ne...