AIMC Topic: Deep Learning

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DAPNet: multi-view graph contrastive network incorporating disease clinical and molecular associations for disease progression prediction.

BMC medical informatics and decision making
BACKGROUND: Timely and accurate prediction of disease progress is crucial for facilitating early intervention and treatment for various chronic diseases. However, due to the complicated and longitudinal nature of disease progression, the capacity and...

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...

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 ...

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...

Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization.

Scientific reports
With the rapid increase of users over social media, cyberbullying, and hate speech problems have arisen over the past years. Automatic hate speech detection (HSD) from text is an emerging research problem in natural language processing (NLP). Researc...

Image biomarkers and explainable AI: handcrafted features versus deep learned features.

European radiology experimental
Feature extraction and selection from medical data are the basis of radiomics and image biomarker discovery for various architectures, including convolutional neural networks (CNNs). We herein describe the typical radiomics steps and the components o...

Artificial intelligence in cytopathological applications for cancer: a review of accuracy and analytic validity.

European journal of medical research
BACKGROUND: Cytopathological examination serves as a tool for diagnosing solid tumors and hematologic malignancies. Artificial intelligence (AI)-assisted methods have been widely discussed in the literature for increasing sensitivity, specificity and...

Evaluation of machine learning and deep learning models for daily air quality index prediction in Delhi city, India.

Environmental monitoring and assessment
The air quality index (AQI), based on criteria for air contaminants, is defined to provide a shared vision of air quality. As air pollution continues to rise in global cities due to urbanization and climate change, air pollution monitoring and foreca...

Advancing dermoscopy through a synthetic hair benchmark dataset and deep learning-based hair removal.

Journal of biomedical optics
SIGNIFICANCE: Early detection of melanoma is crucial for improving patient outcomes, and dermoscopy is a critical tool for this purpose. However, hair presence in dermoscopic images can obscure important features, complicating the diagnostic process....

Two-stage ship detection at long distances based on deep learning and slicing technique.

PloS one
Ship detection over long distances is crucial for the visual perception of intelligent ships. Since traditional image processing-based methods are not robust, deep learning-based image recognition methods can automatically obtain the features of smal...