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Adolescent Brain Cognitive Development Neurocognitive Prediction [[electronic resource] ] : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru
| Adolescent Brain Cognitive Development Neurocognitive Prediction [[electronic resource] ] : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 188 p. 57 illus., 49 illus. in color.) |
| Disciplina | 616.8047548 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Machine learning Mathematical statistics Data mining Image Processing and Computer Vision Machine Learning Probability and Statistics in Computer Science Data Mining and Knowledge Discovery |
| ISBN | 3-030-31901-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction -- Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet -- Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction -- Surface-based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019 -- Prediction of Fluid Intelligence From T1-Weighted Magnetic Resonance Images -- Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI -- Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry -- Predict Fluid Intelligence of Adolescent Using Ensemble Learning -- Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach -- Predicting Fluid intelligence from structural MRI using Random Forest regression -- Nu Support Vector Machine in Prediction of Fluid Intelligence Using MRI Data -- An AutoML Approach for the Prediction of Fluid Intelligence From MRI-Derived Features -- Predicting Fluid Intelligence from MRI images with Encoder-decoder Regularization -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology -- Ensemble Modeling of Neurocognitive Performance Using MRI-derived Brain Structure Volumes -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression -- Predicting fluid intelligence using anatomical measures within functionally defined brain networks -- Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs -- Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction -- Adolescent fluid intelligence prediction from regional brain volumes and cortical curvatures using BlockPC-XGBoost -- Cortical and Subcortical Contributions to Predicting Intelligence using 3D ConvNets. |
| Record Nr. | UNISA-996466429903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Adolescent Brain Cognitive Development Neurocognitive Prediction : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru
| Adolescent Brain Cognitive Development Neurocognitive Prediction : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 188 p. 57 illus., 49 illus. in color.) |
| Disciplina | 616.8047548 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Machine learning Computer science - Mathematics Mathematical statistics Data mining Computer Vision Machine Learning Probability and Statistics in Computer Science Data Mining and Knowledge Discovery |
| ISBN | 3-030-31901-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction -- Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet -- Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction -- Surface-based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019 -- Prediction of Fluid Intelligence From T1-Weighted Magnetic Resonance Images -- Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI -- Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry -- Predict Fluid Intelligence of Adolescent Using Ensemble Learning -- Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach -- Predicting Fluid intelligence from structural MRI using Random Forest regression -- Nu Support Vector Machine in Prediction of Fluid Intelligence Using MRI Data -- An AutoML Approach for the Prediction of Fluid Intelligence From MRI-Derived Features -- Predicting Fluid Intelligence from MRI images with Encoder-decoder Regularization -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology -- Ensemble Modeling of Neurocognitive Performance Using MRI-derived Brain Structure Volumes -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression -- Predicting fluid intelligence using anatomical measures within functionally defined brain networks -- Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs -- Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction -- Adolescent fluid intelligence prediction from regional brain volumes and cortical curvatures using BlockPC-XGBoost -- Cortical and Subcortical Contributions to Predicting Intelligence using 3D ConvNets. |
| Record Nr. | UNINA-9910349275503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning in Medical Imaging [[electronic resource] ] : 7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Li Wang, Ehsan Adeli, Qian Wang, Yinghuan Shi, Heung-Il Suk
| Machine Learning in Medical Imaging [[electronic resource] ] : 7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Li Wang, Ehsan Adeli, Qian Wang, Yinghuan Shi, Heung-Il Suk |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XIV, 324 p. 127 illus.) |
| Disciplina | 006.6 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Health informatics Data mining Artificial intelligence Image Processing and Computer Vision Pattern Recognition Health Informatics Data Mining and Knowledge Discovery Artificial Intelligence |
| ISBN | 3-319-47157-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465662703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Machine Learning in Medical Imaging : 7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Li Wang, Ehsan Adeli, Qian Wang, Yinghuan Shi, Heung-Il Suk
| Machine Learning in Medical Imaging : 7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Li Wang, Ehsan Adeli, Qian Wang, Yinghuan Shi, Heung-Il Suk |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XIV, 324 p. 127 illus.) |
| Disciplina | 006.6 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Health informatics Data mining Artificial intelligence Image Processing and Computer Vision Pattern Recognition Health Informatics Data Mining and Knowledge Discovery Artificial Intelligence |
| ISBN | 3-319-47157-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484925303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Predictive Intelligence in Medicine [[electronic resource] ] : 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas, Ghada Zamzmi
| Predictive Intelligence in Medicine [[electronic resource] ] : 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas, Ghada Zamzmi |
| Autore | Rekik Islem |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (306 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
AdeliEhsan
ParkSang Hyun CintasCelia ZamzmiGhada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN | 3-031-46005-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996558470203316 |
Rekik Islem
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Predictive Intelligence in Medicine [[electronic resource] ] : 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas, Ghada Zamzmi
| Predictive Intelligence in Medicine [[electronic resource] ] : 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas, Ghada Zamzmi |
| Autore | Rekik Islem |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (306 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
AdeliEhsan
ParkSang Hyun CintasCelia ZamzmiGhada |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN | 3-031-46005-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910747595203321 |
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Rekik Islem
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Predictive Intelligence in Medicine [[electronic resource] ] : Second International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park
| Predictive Intelligence in Medicine [[electronic resource] ] : Second International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIII, 178 p. 58 illus., 48 illus. in color.) |
| Disciplina | 610.28563 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Artificial intelligence
Mathematical statistics Optical data processing Algorithms Data mining Artificial Intelligence Probability and Statistics in Computer Science Computer Imaging, Vision, Pattern Recognition and Graphics Algorithm Analysis and Problem Complexity Data Mining and Knowledge Discovery |
| ISBN | 3-030-32281-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | TADPOLE Challenge: Accurate Alzheimer's disease prediction through crowdsourced forecasting of future data -- Inter-fractional Respiratory Motion Modelling from Abdominal Ultrasound: A Feasibility Study -- Adaptive Neuro-Fuzzy Inference System-based Chaotic Swarm Intelligence Hybrid Model for Recognition of Mild Cognitive Impairment from Resting-state fMRI -- Deep Learning via Fused Bidirectional Attention Stacked Long Short-term Memory for Obsessive-Compulsive Disorder Diagnosis and Risk Screening -- Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning -- Predicting Response to the Antidepressant Bupropion using Pretreatment fMRI -- Progressive Infant Brain Connectivity Evolution Prediction from Neonatal MRI using Bidirectionally Supervised Sample Selection -- Computed Tomography Image-Based Deep Survival Regression for Metastatic Colorectal Cancer using a Non-Proportional Hazards Model -- 7 years of Developing Seed Techniques for Alzheimer's Disease Diagnosis using Brain Image and Connectivity Data Largely Bypassed Prediction for Prognosis -- Generative Adversarial Irregularity Detection in Mammography Images -- Hierarchical Adversarial Connectomic Domain Alignment for Target Brain Graph Prediction and Classification From a Source Graph -- Predicting High-Resolution Brain Networks Using Hierarchically Embedded and Aligned Multi-Resolution Neighborhoods -- Catheter Synthesis in X-Ray Fluoroscopy with Generative Adversarial Networks -- Prediction of Clinical Scores for Subjective Cognitive Decline and Mild Cognitive Impairment -- Diagnosis of Parkinsons Disease in Genetic Cohort Patients via Stage-wise Hierarchical Deep Polynomial Ensemble learning -- Automatic Detection of Bowel Disease with Residual Networks -- Support Vector based Autoregressive Mixed Models of Longitudinal Brain Changes and Corresponding Genetics in Alzheimers Disease -- Treatment Response Prediction of Hepatocellular Carcinoma Patients from Abdominal CT Images with Deep Convolutional Neural Networks. |
| Record Nr. | UNISA-996466318603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Predictive Intelligence in Medicine : Second International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park
| Predictive Intelligence in Medicine : Second International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIII, 178 p. 58 illus., 48 illus. in color.) |
| Disciplina | 610.28563 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Artificial intelligence
Mathematical statistics Optical data processing Algorithms Data mining Artificial Intelligence Probability and Statistics in Computer Science Computer Imaging, Vision, Pattern Recognition and Graphics Algorithm Analysis and Problem Complexity Data Mining and Knowledge Discovery |
| ISBN | 3-030-32281-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | TADPOLE Challenge: Accurate Alzheimer's disease prediction through crowdsourced forecasting of future data -- Inter-fractional Respiratory Motion Modelling from Abdominal Ultrasound: A Feasibility Study -- Adaptive Neuro-Fuzzy Inference System-based Chaotic Swarm Intelligence Hybrid Model for Recognition of Mild Cognitive Impairment from Resting-state fMRI -- Deep Learning via Fused Bidirectional Attention Stacked Long Short-term Memory for Obsessive-Compulsive Disorder Diagnosis and Risk Screening -- Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning -- Predicting Response to the Antidepressant Bupropion using Pretreatment fMRI -- Progressive Infant Brain Connectivity Evolution Prediction from Neonatal MRI using Bidirectionally Supervised Sample Selection -- Computed Tomography Image-Based Deep Survival Regression for Metastatic Colorectal Cancer using a Non-Proportional Hazards Model -- 7 years of Developing Seed Techniques for Alzheimer's Disease Diagnosis using Brain Image and Connectivity Data Largely Bypassed Prediction for Prognosis -- Generative Adversarial Irregularity Detection in Mammography Images -- Hierarchical Adversarial Connectomic Domain Alignment for Target Brain Graph Prediction and Classification From a Source Graph -- Predicting High-Resolution Brain Networks Using Hierarchically Embedded and Aligned Multi-Resolution Neighborhoods -- Catheter Synthesis in X-Ray Fluoroscopy with Generative Adversarial Networks -- Prediction of Clinical Scores for Subjective Cognitive Decline and Mild Cognitive Impairment -- Diagnosis of Parkinsons Disease in Genetic Cohort Patients via Stage-wise Hierarchical Deep Polynomial Ensemble learning -- Automatic Detection of Bowel Disease with Residual Networks -- Support Vector based Autoregressive Mixed Models of Longitudinal Brain Changes and Corresponding Genetics in Alzheimers Disease -- Treatment Response Prediction of Hepatocellular Carcinoma Patients from Abdominal CT Images with Deep Convolutional Neural Networks. |
| Record Nr. | UNINA-9910349272903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
PRedictive Intelligence in MEdicine [[electronic resource] ] : First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Islem Rekik, Gozde Unal, Ehsan Adeli, Sang Hyun Park
| PRedictive Intelligence in MEdicine [[electronic resource] ] : First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Islem Rekik, Gozde Unal, Ehsan Adeli, Sang Hyun Park |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XII, 174 p. 72 illus.) |
| Disciplina | 610.28563 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Computer organization Computers Artificial Intelligence Image Processing and Computer Vision Pattern Recognition Computer Systems Organization and Communication Networks Information Systems and Communication Service |
| ISBN | 3-030-00320-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNISA-996466193203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
PRedictive Intelligence in MEdicine : First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Islem Rekik, Gozde Unal, Ehsan Adeli, Sang Hyun Park
| PRedictive Intelligence in MEdicine : First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Islem Rekik, Gozde Unal, Ehsan Adeli, Sang Hyun Park |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XII, 174 p. 72 illus.) |
| Disciplina | 610.28563 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Computer organization Computers Artificial Intelligence Image Processing and Computer Vision Pattern Recognition Computer Systems Organization and Communication Networks Information Systems and Communication Service |
| ISBN | 3-030-00320-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910349406603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||