AI Medical Compendium Topic:
Learning

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Empirical Analysis of Early Childhood Enlightenment Education Using Neural Network.

Computational intelligence and neuroscience
This exploration aims to study the value orientation and essence of early childhood enlightenment education based on the deep neural network (DNN). Based on the acquisition and feature learning of cross-media education big data, the DNN correlation l...

The Use of Thinking Visualization Techniques in College Teaching Based on Improved Genetic Algorithms.

Computational intelligence and neuroscience
Current educational resources do not maximize energy efficiency, and scientific and proven teaching methods are necessary for today's university education to help achieve the integration of teaching resources and improve teaching quality. This study ...

TAFM: A Recommendation Algorithm Based on Text-Attention Factorization Mechanism.

Computational intelligence and neuroscience
The click-through rate (CTR) prediction task is used to estimate the probabilities of users clicking on recommended items, which are extremely important in recommender systems. Recently, the deep factorization machine (DeepFM) algorithm was proposed....

Dual-level diagnostic feature learning with recurrent neural networks for treatment sequence recommendation.

Journal of biomedical informatics
In recent years, the massive electronic medical records (EMRs) have supported the development of intelligent medical services such as treatment recommendations. However, existing treatment recommendations usually follow the traditional sequential rec...

A Bi-level representation learning model for medical visual question answering.

Journal of biomedical informatics
Medical Visual Question Answering (VQA) targets at answering questions related to given medical images and it contains tremendous potential in healthcare services. However, researches on medical VQA are still facing challenges, particularly on how to...

An Improved Load Forecasting Method Based on the Transfer Learning Structure under Cyber-Threat Condition.

Computational intelligence and neuroscience
Smart grid is regarded as an evolutionary regime of existing power grids. It integrates artificial intelligence and communication technologies to fundamentally improve the efficiency and reliability of power systems. One serious challenge for the sma...

Integration of Multi-Head Self-Attention and Convolution for Person Re-Identification.

Sensors (Basel, Switzerland)
Person re-identification is essential to intelligent video analytics, whose results affect downstream tasks such as behavior and event analysis. However, most existing models only consider the accuracy, rather than the computational complexity, which...

Contactless Fall Detection by Means of Multiple Bioradars and Transfer Learning.

Sensors (Basel, Switzerland)
Fall detection in humans is critical in the prevention of life-threatening conditions. This is especially important for elderly people who are living alone. Therefore, automatic fall detection is one of the most relevant problems in geriatrics. Biora...

Multisource-Refined Transfer Network for Industrial Fault Diagnosis Under Domain and Category Inconsistencies.

IEEE transactions on cybernetics
Unsupervised cross-domain fault diagnosis has been actively researched in recent years. It learns transferable features that reduce distribution inconsistency between source and target domains without target supervision. Most of the existing cross-do...

TriATNE: Tripartite Adversarial Training for Network Embeddings.

IEEE transactions on cybernetics
Existing network embedding algorithms based on generative adversarial networks (GANs) improve the robustness of node embeddings by selecting high-quality negative samples with the generator to play against the discriminator. Since most of the negativ...