A robust framework for Alzheimer's disease detection and staging: incorporating multi-feature integration, MRMR feature selection, and Random Forest classification
In advancing Alzheimer's disease detection, this study presents a potent hybrid approach
that leverages sophisticated features. Commencing with the TVL1 norm, the method reduces …
that leverages sophisticated features. Commencing with the TVL1 norm, the method reduces …
DeepDepth: Prediction of O (6)-methylguanine-DNA methyltransferase genotype in glioblastoma patients using multimodal representation learning based on deep …
Abstract Representation learning aims to extract meaningful features from medical images
that are often multimodal, ie, captured using multiple imaging modalities, to provide a more …
that are often multimodal, ie, captured using multiple imaging modalities, to provide a more …
Proposing new seismic texture attributes based on novel gray level matrix with application to salt dome detection
P Soltani, AR Kahoo, H Hasanpour - Journal of Applied Geophysics, 2023 - Elsevier
The exploration of new hydrocarbon resources requires a detailed image of the subsurface
geological structures. Interpreting seismic sections is one of the most common ways of …
geological structures. Interpreting seismic sections is one of the most common ways of …
Application of BP Neural Network and Artificial Intelligence Algorithm in Pharmaceutical Production
L Lin - … on Cognitive based Information Processing and …, 2023 - Springer
Backpropagation neural network (BP neural network) is a new efficient and highly parallel
information processing pattern algorithm. Artificial intelligence algorithms can enable …
information processing pattern algorithm. Artificial intelligence algorithms can enable …