AI Medical Compendium Topic:
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Deep learning for religious and continent-based toxic content detection and classification.

Scientific reports
With time, numerous online communication platforms have emerged that allow people to express themselves, increasing the dissemination of toxic languages, such as racism, sexual harassment, and other negative behaviors that are not accepted in polite ...

Application of Outlier Detection Model in Korean Language and Culture Communication System Based on Artificial Intelligence.

Computational intelligence and neuroscience
With the continuous expansion of the Internet in China, network communication models and network services have become more and more complex, and with the increase of data types and diversification of data sources, network operation and maintenance pr...

Investigation on Deep Learning Model of College English Based on Multimodal Learning Method.

Computational intelligence and neuroscience
Deep learning refers to active learning that allows students to perceive, experience, understand, and apply knowledge. Deep learning focuses on the mastery of knowledge and skills and more on the cultivation of higher-order thinking skills such as aw...

Method for Quantum Denoisers Using Convolutional Neural Network.

Computational intelligence and neuroscience
In many applications of quantum information science, high-dimensional entanglement is needed. Quantum teleportation is used for transferring information from one place to another using Einstein-Podolsk-Rosen pairs (EPR) and two classical bits of comm...

A Multimodel-Based Deep Learning Framework for Short Text Multiclass Classification with the Imbalanced and Extremely Small Data Set.

Computational intelligence and neuroscience
Text classification plays an important role in many practical applications. In the real world, there are extremely small datasets. Most existing methods adopt pretrained neural network models to handle this kind of dataset. However, these methods are...

Single-sequence protein structure prediction using a language model and deep learning.

Nature biotechnology
AlphaFold2 and related computational systems predict protein structure using deep learning and co-evolutionary relationships encoded in multiple sequence alignments (MSAs). Despite high prediction accuracy achieved by these systems, challenges remain...

Modeling Trajectories Obtained from External Sensors for Location Prediction via NLP Approaches.

Sensors (Basel, Switzerland)
Representation learning seeks to extract useful and low-dimensional attributes from complex and high-dimensional data. Natural language processing (NLP) was used to investigate the representation learning models to extract words' feature vectors usin...

PICO entity extraction for preclinical animal literature.

Systematic reviews
BACKGROUND: Natural language processing could assist multiple tasks in systematic reviews to reduce workflow, including the extraction of PICO elements such as study populations, interventions, comparators and outcomes. The PICO framework provides a ...

Construction and Computation of the College English Teaching Path in the Artificial Intelligence Teaching Environment.

Computational intelligence and neuroscience
Today, English is the world's main international language and is widely spoken. In this context, the learning of English has long been valued by all countries. In addition, English plays an essential role in the process of economic globalization, spe...

Deep Learning-Based Classification of Spoken English Digits.

Computational intelligence and neuroscience
Classification of isolated digits is the basic challenge for many speech classification systems. While a lot of work has been carried out on spoken languages, only limited research work on spoken English digit data has been reported in the literature...