Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Islem Rekik | - |
| dc.contributor.author | Gozde Unal | - |
| dc.contributor.author | Ehsan Adeli | - |
| dc.contributor.author | Sang Hyun Park | - |
| dc.date.accessioned | 2019-08-01T16:00:23Z | - |
| dc.date.available | 2019-08-01T16:00:23Z | - |
| dc.date.issued | 2018 | - |
| dc.identifier.isbn | 2147483647 | - |
| dc.identifier.uri | http://hdl.handle.net/20.500.11750/10339 | - |
| dc.identifier.uri | https://doi.org/10.1007/978-3-030-00320-3 | - |
| dc.description.statementofresponsibility | edited by Islem Rekik, Gozde Unal, Ehsan Adeli, Sang Hyun Park. | - |
| dc.description.tableofcontents | Computer Aided Identification of Motion Disturbances Related to Parkinson's Disease -- Prediction of Severity and Treatment Outcome for ASD from fMRI -- Enhancement of Perivascular Spaces Using a Very Deep 3D Dense Network -- Generation of Amyloid PET Images via Conditional Adversarial Training for Predicting Progression to Alzheimer's Disease -- Prediction of Hearing Loss Based on Auditory Perception: A Preliminary Study -- Predictive Patient Care: Survival Model to Prevent Medication Non-adherence -- Joint Robust Imputation and Classification for Early Dementia Detection Using Incomplete Multi-Modality Data -- Shared Latent Structures Between Imaging Features and Biomarkers in Early Stages of Alzheimer's Disease -- Predicting Nucleus Basalis of Meynert Volume from Compartmental Brain Segmentations -- Multi-modal Neuroimaging Data Fusion via Latent Space Learning for Alzheimer's Disease Diagnosis -- Transfer Learning for Task Adaptation of Brain Lesion Assessment and Prediction of Brain Abnormalities Progression/Regression Using Irregularity Age Map in Brain MRI -- Multi-View Brain Network Prediction From a Source View Using Sample Selection via CCA-based Multi-Kernel Connectomic Manifold Learning -- Predicting Emotional Intelligence Scores From Multi-Session Functional Brain Connectomes -- Predictive Modeling of Longitudinal Data for Alzheimer's Disease Diagnosis Using RNNs -- Towards Continuous Health Diagnosis from Faces with Deep Learning -- XmoNet: A Fully Convolutional Network for Cross-Modality MR Image Inference -- 3D Convolutional Neural Network and Stacked Bidirectional Recurrent Neural Network for Alzheimer's Disease Diagnosis -- Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI -- Diffusion MRI Spatial Super-Resolution Using Generative Adversarialv Networks -- Prediction to Atrial Fibrillation Using Deep Convolutional Neural Networks. | - |
| dc.format.extent | xii, 174 | - |
| dc.language | English | - |
| dc.publisher | Springer | - |
| dc.relation.ispartofseries | Lecture Notes in Computer Science Series 11121 | - |
| dc.subject.lcc | Q334-342TA1637-1638T | - |
| dc.title | PRedictive Intelligence in MEdicine: First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings | - |
| dc.type | Book | - |
| dc.publisher.location | United States | - |
| dc.subject.keyword | Artificial intelligence | - |
| dc.subject.keyword | Classification | - |
| dc.subject.keyword | Classification accuracy | - |
| dc.subject.keyword | Computer vision | - |
| dc.subject.keyword | Feature selection | - |
| dc.subject.keyword | Health informatics | - |
| dc.subject.keyword | Image analysis | - |
| dc.subject.keyword | Image and video acquisition | - |
| dc.subject.keyword | Image processing | - |
| dc.subject.keyword | Machine learning | - |
| dc.subject.keyword | Medical technologies | - |
| dc.subject.keyword | Neural Networks | - |
| dc.subject.keyword | Pattern recognition | - |
| dc.subject.keyword | Prediction | - |
| dc.subject.keyword | Support Vector Machines (SVM) | - |
| dc.contributor.affiliatedAuthor | Park, Sang Hyun | - |
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