AIMC Topic: Neural Networks, Computer

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Early multi-cancer detection through deep learning: An anomaly detection approach using Variational Autoencoder.

Journal of biomedical informatics
Cancer is a disease that causes many deaths worldwide. The treatment of cancer is first and foremost a matter of detection, a treatment that is most effective when the disease is detected at an early stage. With the evolution of technology, several c...

Identification of movie encoding neurons enables movie recognition AI.

Proceedings of the National Academy of Sciences of the United States of America
Natural visual scenes are dominated by spatiotemporal image dynamics, but how the visual system integrates "movie" information over time is unclear. We characterized optic tectal neuronal receptive fields using sparse noise stimuli and reverse correl...

A Novel and Powerful Dual-Stream Multi-Level Graph Convolution Network for Emotion Recognition.

Sensors (Basel, Switzerland)
Emotion recognition enables machines to more acutely perceive and understand users' emotional states, thereby offering more personalized and natural interactive experiences. Given the regularity of the responses of brain activity to human cognitive p...

AI-Aided Gait Analysis with a Wearable Device Featuring a Hydrogel Sensor.

Sensors (Basel, Switzerland)
Wearable devices have revolutionized real-time health monitoring, yet challenges persist in enhancing their flexibility, weight, and accuracy. This paper presents the development of a wearable device employing a conductive polyacrylamide-lithium chlo...

Application of Machine Learning and Deep Neural Visual Features for Predicting Adult Obesity Prevalence in Missouri.

International journal of environmental research and public health
This research study investigates and predicts the obesity prevalence in Missouri, utilizing deep neural visual features extracted from medium-resolution satellite imagery (Sentinel-2). By applying a deep convolutional neural network (DCNN), the study...

Deep-m5U: a deep learning-based approach for RNA 5-methyluridine modification prediction using optimized feature integration.

BMC bioinformatics
BACKGROUND: RNA 5-methyluridine (m5U) modifications play a crucial role in biological processes, making their accurate identification a key focus in computational biology. This paper introduces Deep-m5U, a robust predictor designed to enhance the pre...

Analysis and prediction of infectious diseases based on spatial visualization and machine learning.

Scientific reports
Infectious diseases are a global public health problem that poses a threat to human society. Since the 1970s, constantly mutated new infectious viruses have been quietly attacking humanity, and at least one new type of infectious disease is discovere...

Application of social media communication for museum based on the deep mediatization and artificial intelligence.

Scientific reports
Based on deep mediatization theory and artificial intelligence (AI) technology, this study explores the effective improvement of museums' social media communication by applying Convolutional Neural Network (CNN) technology. Firstly, the social media ...

XAI-driven CatBoost multi-layer perceptron neural network for analyzing breast cancer.

Scientific reports
Early diagnosis of breast cancer is exceptionally important in signifying the treatment results, of women's health. The present study outlines a novel approach for analyzing breast cancer data by using the CatBoost classification model with a multi-l...

Convolutional neural network for oral cancer detection combined with improved tunicate swarm algorithm to detect oral cancer.

Scientific reports
Early Diagnosis of oral cancer is very important and can save you from some oral malignancies. However, while this approach aids in the rapid healing of patients and the preservation of their lives, there are several causes for poor and wrong diagnos...