Machine learning and deep learning: A review of methods and applications
K Sharifani, M Amini - World Information Technology and …, 2023 - papers.ssrn.com
Abstract Machine learning and deep learning have rapidly emerged as powerful tools in
many fields, including image and speech recognition, natural language processing, and …
many fields, including image and speech recognition, natural language processing, and …
Vision transformers in medical computer vision—A contemplative retrospection
Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …
contained within images, have evolved as one of the most contemporary and dominant …
[HTML][HTML] Unified focal loss: Generalising dice and cross entropy-based losses to handle class imbalanced medical image segmentation
Automatic segmentation methods are an important advancement in medical image analysis.
Machine learning techniques, and deep neural networks in particular, are the state-of-the-art …
Machine learning techniques, and deep neural networks in particular, are the state-of-the-art …
[HTML][HTML] Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability
Abstract Machine learning algorithms enable advanced decision making in contemporary
intelligent systems. Research indicates that there is a tradeoff between their model …
intelligent systems. Research indicates that there is a tradeoff between their model …
[HTML][HTML] Making radiomics more reproducible across scanner and imaging protocol variations: a review of harmonization methods
Radiomics converts medical images into mineable data via a high-throughput extraction of
quantitative features used for clinical decision support. However, these radiomic features are …
quantitative features used for clinical decision support. However, these radiomic features are …
Smart data processing for energy harvesting systems using artificial intelligence
Recent substantial advancements in computational techniques, particularly in artificial
intelligence (AI) and machine learning (ML), have raised the demand for smart self-powered …
intelligence (AI) and machine learning (ML), have raised the demand for smart self-powered …
[HTML][HTML] Accelerating 3D printing of pharmaceutical products using machine learning
Abstract Three-dimensional printing (3DP) has seen growing interest within the healthcare
industry for its ability to fabricate personalized medicines and medical devices. However, it …
industry for its ability to fabricate personalized medicines and medical devices. However, it …
[HTML][HTML] On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Data augmentation and transfer learning for brain tumor detection in magnetic resonance imaging
A Anaya-Isaza, L Mera-Jiménez - IEEE Access, 2022 - ieeexplore.ieee.org
The exponential growth of deep learning networks has allowed us to tackle complex tasks,
even in fields as complicated as medicine. However, using these models requires a large …
even in fields as complicated as medicine. However, using these models requires a large …
Deep Convolutional Spiking Neural Network optimized with Arithmetic optimization algorithm for lung disease detection using chest X-ray images
Lung disease is a most common disease all over the world. A numerous feature extraction
with classification models were discussed previously about the lung disease, but those …
with classification models were discussed previously about the lung disease, but those …