Xinwu Yang
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View article: EfficientUNet: An efficient solution for breast tumour segmentation in ultrasound images
EfficientUNet: An efficient solution for breast tumour segmentation in ultrasound images Open
The accurate segmentation of breast tumours is important for the diagnosis and treatment of breast cancer. When using the classic U‐Net, Attention‐UNet, and UNet++ to segment the tumour, there are problems of oversegmentation, incorrect se…
View article: A cGAN-based tumor segmentation method for breast ultrasound images
A cGAN-based tumor segmentation method for breast ultrasound images Open
Objective . This paper proposes a conditional GAN (cGAN)-based method to perform data enhancement of ultrasound images and segmentation of tumors in breast ultrasound images, which improves the reality of the enhenced breast ultrasound ima…
View article: Predicting metal-organic frameworks as catalysts to fix carbon dioxide to cyclic carbonate by machine learning
Predicting metal-organic frameworks as catalysts to fix carbon dioxide to cyclic carbonate by machine learning Open
The process of discovering and developing new materials currently requires considerable effort, time, and expense. Machine learning (ML) algorithms can potentially provide quick and accurate methods for screening new materials. In the pres…
View article: An Effective Dual Self-Attention Residual Network for Seizure Prediction
An Effective Dual Self-Attention Residual Network for Seizure Prediction Open
As one of the most challenging data analysis tasks in chronic brain diseases, epileptic seizure prediction has attracted extensive attention from many researchers. Seizure prediction, can greatly improve patients' quality of life in many w…
View article: Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts
Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts Open
Background Bronchoscopy for suspected lung cancer has low diagnostic sensitivity, rendering many inconclusive results. The Bronchial Genomic Classifier (BGC) was developed to help with patient management by identifying those with low risk …
View article: Additional file 3 of Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts
Additional file 3 of Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts Open
Additional file 3. Gene Ontology biological processes overrepresented in gene modules identified from the gene co-expression network.)
View article: Additional file 2 of Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts
Additional file 2 of Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts Open
Additional file 2. Cell type signature gene lists.
View article: An Improved multi-objective genetic algorithm based on orthogonal design and adaptive clustering pruning strategy
An Improved multi-objective genetic algorithm based on orthogonal design and adaptive clustering pruning strategy Open
Two important characteristics of multi-objective evolutionary algorithms are distribution and convergency. As a classic multi-objective genetic algorithm, NSGA-II is widely used in multi-objective optimization fields. However, in NSGA-II, …