AIMC Topic: Semantics

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Semantic Clinical Artificial Intelligence vs Native Large Language Model Performance on the USMLE.

JAMA network open
IMPORTANCE: Large language models (LLMs) are being implemented in health care. Enhanced accuracy and methods to maintain accuracy over time are needed to maximize LLM benefits.

Bidirectional Semantic Consistency Guided Contrastive Embedding for Generative Zero-Shot Learning.

Neural networks : the official journal of the International Neural Network Society
Generative zero-shot learning methods synthesize features for unseen classes by learning from image features and class semantic vectors, effectively addressing bias in transferring knowledge from seen to unseen classes. However, existing methods dire...

AESeg: Affinity-enhanced segmenter using feature class mapping knowledge distillation for efficient RGB-D semantic segmentation of indoor scenes.

Neural networks : the official journal of the International Neural Network Society
Recent advances in deep learning for semantic segmentation models have introduced dynamic segmentation methods as opposed to static segmentation methods represented by full convolutional networks. Dynamic prediction methods replace static classifiers...

SS-DTI: A deep learning method integrating semantic and structural information for drug-target interaction prediction.

Journal of bioinformatics and computational biology
Drug-target interaction (DTI) prediction is pivotal in drug discovery and repurposing, providing a more efficient alternative to traditional wet-lab experiments by saving time and resources and expediting the identification of potential targets. Curr...

Optimising window size of semantic of classification model for identification of in-text citations based on context and intent.

PloS one
Citations in scientific literature act as channels for the sharing, transfer, and development of scientific knowledge. However, not all citations hold the same significance. Numerous taxonomies and machine learning models have been developed to analy...

Digital evolution: Novo Nordisk's shift to ontology-based data management.

Journal of biomedical semantics
The amount of biomedical data is growing, and managing it is increasingly challenging. While Findable, Accessible, Interoperable and Reusable (FAIR) data principles provide guidance, their adoption has proven difficult, especially in larger enterpris...

Stagger Network: Rethinking information loss in medical image segmentation with various-sized targets.

Neural networks : the official journal of the International Neural Network Society
Medical image segmentation presents the challenge of segmenting various-size targets, demanding the model to effectively capture both local and global information. Despite recent efforts using CNNs and ViTs to predict annotations of different scales,...

Real-world insights of patient voices with age-related macular degeneration in the Republic of Korea and Taiwan: an AI-based Digital Listening study by Semantic-Natural Language Processing.

BMC medical informatics and decision making
BACKGROUND: In this era of active online communication, patients increasingly share their healthcare experiences, concerns, and needs across digital platforms. Leveraging these vast repositories of real-world information, Digital Listening enables th...

Histopathology image classification based on semantic correlation clustering domain adaptation.

Artificial intelligence in medicine
Deep learning has been successfully applied to histopathology image classification tasks. However, the performance of deep models is data-driven, and the acquisition and annotation of pathological image samples are difficult, which limit the model's ...

Comparing neural language models for medical concept representation and patient trajectory prediction.

Artificial intelligence in medicine
Effective representation of medical concepts is crucial for secondary analyses of electronic health records. Neural language models have shown promise in automatically deriving medical concept representations from clinical data. However, the comparat...