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Semantics

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Deep learning-based semantic segmentation of non-melanocytic skin tumors in whole-slide histopathological images.

Experimental dermatology
Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the two most common skin cancer and impose a huge medical burden on society. Histopathological examination based on whole-slide images (WSIs) remains to be the confirmatory diagnostic m...

Improving Biomedical Question Answering by Data Augmentation and Model Weighting.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical Question Answering aims to extract an answer to the given question from a biomedical context. Due to the strong professionalism of specific domain, it's more difficult to build large-scale datasets for specific domain question answering. E...

Deep-learning-based semantic segmentation of autonomic nerves from laparoscopic images of colorectal surgery: an experimental pilot study.

International journal of surgery (London, England)
BACKGROUND: The preservation of autonomic nerves is the most important factor in maintaining genitourinary function in colorectal surgery; however, these nerves are not clearly recognisable, and their identification is strongly affected by the surgic...

Overlap in meaning is a stronger predictor of semantic activation in GPT-3 than in humans.

Scientific reports
Modern large language models generate texts that are virtually indistinguishable from those written by humans and achieve near-human performance in comprehension and reasoning tests. Yet, their complexity makes it difficult to explain and predict the...

Developing a Knowledge Graph for Pharmacokinetic Natural Product-Drug Interactions.

Journal of biomedical informatics
BACKGROUND: Pharmacokinetic natural product-drug interactions (NPDIs) occur when botanical or other natural products are co-consumed with pharmaceutical drugs. With the growing use of natural products, the risk for potential NPDIs and consequent adve...

Optimization Algorithm of Moving Object Detection Using Multiscale Pyramid Convolutional Neural Networks.

Computational intelligence and neuroscience
Object detection and recognition is a very important topic with significant research value. This research develops an optimised model of moving target identification based on CNN to address the issues of insufficient positioning information and low t...

EG-TransUNet: a transformer-based U-Net with enhanced and guided models for biomedical image segmentation.

BMC bioinformatics
Although various methods based on convolutional neural networks have improved the performance of biomedical image segmentation to meet the precision requirements of medical imaging segmentation task, medical image segmentation methods based on deep l...

Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts.

Scientific reports
How do we make sense of the input from our sensory organs, and put the perceived information into context of our past experiences? The hippocampal-entorhinal complex plays a major role in the organization of memory and thought. The formation of and n...

Marine ship instance segmentation by deep neural networks using a global and local attention (GALA) mechanism.

PloS one
Marine ships are the transport vehicle in the ocean and instance segmentation of marine ships is an accurate and efficient analysis approach to achieve a quantitative understanding of marine ships, for example, their relative locations to other ships...

Lifelong Text-Audio Sentiment Analysis learning.

Neural networks : the official journal of the International Neural Network Society
Sentiment analysis refers to the mining of textual context, which is conducted with the aim of identifying and extracting subjective opinions in textual materials. However, most existing methods neglect other important modalities, e.g., the audio mod...