Prediction of outcome in Parkinson’s disease patients from DAT SPECT images using a convolutional neural network
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- Type
- article
- Published
- 2018-11-01
- Cited by
- 12
- References
- 10
- OpenAlex
- https://openalex.org/W2972025743
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:201847194
Keywords
Convolutional neural network, Artificial intelligence, Rating scale, Parkinson's disease, Computer science
References
- Multi-scale Convolutional Neural Networks for Lung Nodule Classification
- SPECT Molecular Imaging in Parkinson's Disease
- Cross‐Validatory Choice and Assessment of Statistical Predictions
- TensorFlow: a system for large-scale machine learning
- Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction
- Improved prediction of outcome in Parkinson's disease using radiomics analysis of longitudinal DAT SPECT images
- Data Analysis Strategies in Medical Imaging
- Multimodal Radiomic Features for the Predicting Gleason Score of Prostate Cancer
- Refining diagnosis of Parkinson's disease with deep learning-based interpretation of dopamine transporter imaging
- Adam: A Method for Stochastic Optimization
- NeuroImage: Clinical
- TensorFlow: A system for large-scale machine learning
- This Paper Is Included in the Proceedings of the 12th Usenix Symposium on Operating Systems Design and Implementation (osdi '16). Tensorflow: a System for Large-scale Machine Learning Tensorflow: a System for Large-scale Machine Learning
Cited by
- Machine Learning Methods for Optimal Prediction of Outcome in Parkinson’s Disease
- Machine learning methods for optimal prediction of motor outcome in Parkinson's disease.
- Improved motor outcome prediction in Parkinson's disease applying deep learning to DaTscan SPECT images
- The Role of Neural Network for the Detection of Parkinson’s Disease: A Scoping Review
- An Early Prediction of Parkinson’s Disease Using Facial Emotional Recognition
- Soft Attention Based DenseNet Model for Parkinson’s Disease Classification Using SPECT Images
- Molecular Imaging in Parkinsonian Disorders—What’s New and Hot?
- Deep Convolutional Neural Networks for Diagnosis of Parkinson’s Disease Using MRI Data
- Role of Artificial Intelligence Techniques and Neuroimaging Modalities in Detection of Parkinson’s Disease: A Systematic Review
- Fox- Based Feature Selection Algorithm for Detection of Parkinson's Disease
- Parkinson’s Disease Detection using SPECT Images and Artificial Neural Network for Classification
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