Alcoholism identification via convolutional neural network based on parametric ReLU, dropout, and batch normalization
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3924-0
Abstract: Alcoholism changes the structure of brain. Several somatic marker hypothesis network-related regions are known to be damaged in chronic alcoholism. Neuroimaging approach can help us better understanding the impairment discovered in alcohol-dependent subjects. In this… read more here.
Keywords: batch normalization; alcoholism; network; dropout ... See more keywords
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization
Sign Up to like & getrecommendations! Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-24464-3
Abstract: Unmasking the decision making process of machine learning models is essential for implementing diagnostic support systems in clinical practice. Here, we demonstrate that adversarially trained models can significantly enhance the usability of pathology detection as… read more here.
Keywords: diagnostic performance; batch normalization; batch; advancing diagnostic ... See more keywords
Protein-Protein Interaction Sites Prediction Using Batch Normalization Based CNNs and Oversampling Method Borderline-SMOTE.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2023.3238001
Abstract: The recognition of protein-protein interaction sites (PPIs) is beneficial for the interpretation of protein functions and the development of new drugs. Traditional biological experiments to identify PPI sites are expensive and inefficient, leading to the… read more here.
Keywords: protein protein; borderline smote; interaction sites; protein interaction ... See more keywords
BNET: Batch Normalization With Enhanced Linear Transformation.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2023.3235369
Abstract: Batch normalization (BN) is a fundamental unit in modern deep neural networks. However, BN and its variants focus on normalization statistics but neglect the recovery step that uses linear transformation to improve the capacity of… read more here.
Keywords: normalization; batch normalization; bnet; linear transformation ... See more keywords
Multiple Sclerosis Identification by 14-Layer Convolutional Neural Network With Batch Normalization, Dropout, and Stochastic Pooling
Sign Up to like & getrecommendations! Published in 2018 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2018.00818
Abstract: Aim: Multiple sclerosis is a severe brain and/or spinal cord disease. It may lead to a wide range of symptoms. Hence, the early diagnosis and treatment is quite important. Method: This study proposed a 14-layer… read more here.
Keywords: layer convolutional; stochastic pooling; convolutional neural; multiple sclerosis ... See more keywords