Autor Park, Sang Hyun
|
|
Documentos disponibles escritos por este autor (4)
Hacer una sugerencia Refinar búsquedaPredictive Intelligence in Medicine / Rekik, Islem ; Adeli, Ehsan ; Park, Sang Hyun ; Schnabel, Julia
Título : Predictive Intelligence in Medicine : 4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings Tipo de documento: documento electrónico Autores: Rekik, Islem, ; Adeli, Ehsan, ; Park, Sang Hyun, ; Schnabel, Julia, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2021 Número de páginas: XIII, 280 p. 80 ilustraciones, 68 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-87602-9 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Palabras clave: Inteligencia artificial Bioinformática Biología Computacional y de Sistemas Ingeniería Informática y Redes Red informática Ingeniería Informática Visión por computador Visión Procesamiento de imágenes Índice Dewey: 006.3 Inteligencia artificial Resumen: Este libro constituye las actas del 4.º Taller Internacional sobre Inteligencia Predictiva en Medicina, PRIME 2021, celebrado junto con MICCAI 2021, en Estrasburgo, Francia, en octubre de 2021.* Los 25 artículos presentados en este volumen fueron cuidadosamente revisados y seleccionados para su inclusión. en este libro. Las contribuciones describen nuevos modelos y métodos predictivos de vanguardia que resuelven problemas desafiantes en el campo médico para una medicina predictiva de alta precisión. *El taller se realizó de manera virtual. Nota de contenido: Self-Supervised Learning based CT Denoising using Pseudo-CT Image Pairs -- A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint -- One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction -- Mixing-AdaSIN: Constructing a De-biased Dataset using Adaptive Structural Instance Normalization and Texture Mixing -- Liver Tumor Localization and Characterization from Multi-Phase MR Volumes Using Key-Slice Prediction: A Physician-Inspired Approach -- Improving Tuberculosis Recognition on Bone-Suppressed Chest X-rays Guided by Task-Specific Features -- Template-Based Inter-modality Super-resolution of Brain Connectivity -- Adversarial Bayesian Optimization for Quantifying Motion Artifact within MRI -- False Positive Suppression in Cervical Cell Screening via Attention-Guided Semi-Supervised Learning -- Investigating and Quantifying the Reproducibility of Graph Neural Networks in Predictive Medicine -- Self Supervised Contrastive Learning on Multiple Breast Modalities Boosts Classification Performance -- Self-Guided Multi-Attention Network for Periventricular Leukomalacia Recognition -- Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray -- Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer -- Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network -- Probabilistic Deep Learning with Adversarial Training and Volume Interval Estimation – Better Ways to Perform and Evaluate Predictive Models for White Matter Hyperintensities Evolution -- A Multi-scale Capsule Network for Improving Diagnostic Generalizability in Breast Cancer Diagnosis using Ultrasonography -- Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy using Multi-scale Patch Learning with Mammography -- The Pitfalls of SampleSelection: A Case Study on Lung Nodule Classification -- Anatomical Structure-aware Pulmonary Nodule Detection via Parallel Multi-Task RoI Head -- Towards Cancer Patients Classification Using Liquid Biopsy -- Foreseeing Survival through `Fuzzy Intelligence': A cognitively-inspired incremental learning based de novo model for Breast Cancer Prognosis by multi-omics data fusion -- Improving Across Dataset Brain Age Predictions using Transfer Learning -- Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation -- FLAT-Net: Longitudinal Brain Graph Evolution Prediction from a Few Training Representative Templates. En línea: https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Link: https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i Predictive Intelligence in Medicine : 4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings [documento electrónico] / Rekik, Islem, ; Adeli, Ehsan, ; Park, Sang Hyun, ; Schnabel, Julia, . - 1 ed. . - [s.l.] : Springer, 2021 . - XIII, 280 p. 80 ilustraciones, 68 ilustraciones en color.
ISBN : 978-3-030-87602-9
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Palabras clave: Inteligencia artificial Bioinformática Biología Computacional y de Sistemas Ingeniería Informática y Redes Red informática Ingeniería Informática Visión por computador Visión Procesamiento de imágenes Índice Dewey: 006.3 Inteligencia artificial Resumen: Este libro constituye las actas del 4.º Taller Internacional sobre Inteligencia Predictiva en Medicina, PRIME 2021, celebrado junto con MICCAI 2021, en Estrasburgo, Francia, en octubre de 2021.* Los 25 artículos presentados en este volumen fueron cuidadosamente revisados y seleccionados para su inclusión. en este libro. Las contribuciones describen nuevos modelos y métodos predictivos de vanguardia que resuelven problemas desafiantes en el campo médico para una medicina predictiva de alta precisión. *El taller se realizó de manera virtual. Nota de contenido: Self-Supervised Learning based CT Denoising using Pseudo-CT Image Pairs -- A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint -- One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction -- Mixing-AdaSIN: Constructing a De-biased Dataset using Adaptive Structural Instance Normalization and Texture Mixing -- Liver Tumor Localization and Characterization from Multi-Phase MR Volumes Using Key-Slice Prediction: A Physician-Inspired Approach -- Improving Tuberculosis Recognition on Bone-Suppressed Chest X-rays Guided by Task-Specific Features -- Template-Based Inter-modality Super-resolution of Brain Connectivity -- Adversarial Bayesian Optimization for Quantifying Motion Artifact within MRI -- False Positive Suppression in Cervical Cell Screening via Attention-Guided Semi-Supervised Learning -- Investigating and Quantifying the Reproducibility of Graph Neural Networks in Predictive Medicine -- Self Supervised Contrastive Learning on Multiple Breast Modalities Boosts Classification Performance -- Self-Guided Multi-Attention Network for Periventricular Leukomalacia Recognition -- Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray -- Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer -- Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network -- Probabilistic Deep Learning with Adversarial Training and Volume Interval Estimation – Better Ways to Perform and Evaluate Predictive Models for White Matter Hyperintensities Evolution -- A Multi-scale Capsule Network for Improving Diagnostic Generalizability in Breast Cancer Diagnosis using Ultrasonography -- Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy using Multi-scale Patch Learning with Mammography -- The Pitfalls of SampleSelection: A Case Study on Lung Nodule Classification -- Anatomical Structure-aware Pulmonary Nodule Detection via Parallel Multi-Task RoI Head -- Towards Cancer Patients Classification Using Liquid Biopsy -- Foreseeing Survival through `Fuzzy Intelligence': A cognitively-inspired incremental learning based de novo model for Breast Cancer Prognosis by multi-omics data fusion -- Improving Across Dataset Brain Age Predictions using Transfer Learning -- Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation -- FLAT-Net: Longitudinal Brain Graph Evolution Prediction from a Few Training Representative Templates. En línea: https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Link: https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i
Título : PRedictive Intelligence in MEdicine : First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings Tipo de documento: documento electrónico Autores: Rekik, Islem, ; Unal, Gozde, ; Adeli, Ehsan, ; Park, Sang Hyun, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2018 Número de páginas: XII, 174 p. 72 ilustraciones ISBN/ISSN/DL: 978-3-030-00320-3 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Palabras clave: Visión por computador Redes de comunicación informática Ingeniería Informática y Redes Reconocimiento de patrones automatizado Inteligencia artificial Red informática Sistemas de reconocimiento de patrones Ingeniería Informática Índice Dewey: 006.3 Inteligencia artificial Resumen: Este libro constituye las actas arbitradas del Primer Taller Internacional sobre Inteligencia Predictiva en Medicina, PRIME 2018, celebrado junto con MICCAI 2018, en Granada, España, en septiembre de 2018. Los 20 artículos completos presentados fueron cuidadosamente revisados y seleccionados entre 23 presentaciones. El principal objetivo del taller es impulsar la aparición de modelos predictivos en un sentido amplio, con aplicación a datos médicos. En particular, el taller admitirá artículos que describan nuevos modelos y métodos predictivos de vanguardia que resuelven problemas desafiantes en el campo médico. Nota de contenido: 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. En línea: https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Link: https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i PRedictive Intelligence in MEdicine : First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings [documento electrónico] / Rekik, Islem, ; Unal, Gozde, ; Adeli, Ehsan, ; Park, Sang Hyun, . - 1 ed. . - [s.l.] : Springer, 2018 . - XII, 174 p. 72 ilustraciones.
ISBN : 978-3-030-00320-3
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Palabras clave: Visión por computador Redes de comunicación informática Ingeniería Informática y Redes Reconocimiento de patrones automatizado Inteligencia artificial Red informática Sistemas de reconocimiento de patrones Ingeniería Informática Índice Dewey: 006.3 Inteligencia artificial Resumen: Este libro constituye las actas arbitradas del Primer Taller Internacional sobre Inteligencia Predictiva en Medicina, PRIME 2018, celebrado junto con MICCAI 2018, en Granada, España, en septiembre de 2018. Los 20 artículos completos presentados fueron cuidadosamente revisados y seleccionados entre 23 presentaciones. El principal objetivo del taller es impulsar la aparición de modelos predictivos en un sentido amplio, con aplicación a datos médicos. En particular, el taller admitirá artículos que describan nuevos modelos y métodos predictivos de vanguardia que resuelven problemas desafiantes en el campo médico. Nota de contenido: 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. En línea: https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Link: https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i
Título : Predictive Intelligence in Medicine : Second International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings Tipo de documento: documento electrónico Autores: Rekik, Islem, ; Adeli, Ehsan, ; Park, Sang Hyun, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XIII, 178 p. 58 ilustraciones, 48 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-32281-6 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Palabras clave: Visión Probabilidad y Estadística en Informática Inteligencia artificial Procesamiento de datos Algoritmo Procesamiento de imágenes Matemáticas Informática Minería de datos y descubrimiento de conocimientos Visión por computador Índice Dewey: 006.3 Inteligencia artificial Resumen: Este libro constituye las actas del Segundo Taller Internacional sobre Inteligencia Predictiva en Medicina, PRIME 2019, celebrado junto con MICCAI 2019, en Shenzhen, China, en octubre de 2019. Los 18 artículos presentados en este volumen fueron cuidadosamente revisados y seleccionados para su inclusión en este libro. Las contribuciones describen nuevos modelos y métodos predictivos de vanguardia que resuelven problemas desafiantes en el campo médico para una medicina predictiva de alta precisión. . Nota de contenido: 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. En línea: https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Link: https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i Predictive Intelligence in Medicine : Second International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings [documento electrónico] / Rekik, Islem, ; Adeli, Ehsan, ; Park, Sang Hyun, . - 1 ed. . - [s.l.] : Springer, 2019 . - XIII, 178 p. 58 ilustraciones, 48 ilustraciones en color.
ISBN : 978-3-030-32281-6
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Palabras clave: Visión Probabilidad y Estadística en Informática Inteligencia artificial Procesamiento de datos Algoritmo Procesamiento de imágenes Matemáticas Informática Minería de datos y descubrimiento de conocimientos Visión por computador Índice Dewey: 006.3 Inteligencia artificial Resumen: Este libro constituye las actas del Segundo Taller Internacional sobre Inteligencia Predictiva en Medicina, PRIME 2019, celebrado junto con MICCAI 2019, en Shenzhen, China, en octubre de 2019. Los 18 artículos presentados en este volumen fueron cuidadosamente revisados y seleccionados para su inclusión en este libro. Las contribuciones describen nuevos modelos y métodos predictivos de vanguardia que resuelven problemas desafiantes en el campo médico para una medicina predictiva de alta precisión. . Nota de contenido: 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. En línea: https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Link: https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i
Título : Predictive Intelligence in Medicine : Third International Workshop, PRIME 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings Tipo de documento: documento electrónico Autores: Rekik, Islem, ; Adeli, Ehsan, ; Park, Sang Hyun, ; Valdés Hernández, Maria del C., Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2020 Número de páginas: XII, 212 p. 65 ilustraciones ISBN/ISSN/DL: 978-3-030-59354-4 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Palabras clave: Ingeniería Informática y Redes Visión Entornos informáticos Red informática Inteligencia artificial Visión por computador Procesamiento de imágenes Ordenador Ingeniería Informática Aplicaciones informáticas y de sistemas de información Índice Dewey: 006.3 Inteligencia artificial Resumen: Este libro constituye las actas del Tercer Taller Internacional sobre Inteligencia Predictiva en Medicina, PRIME 2020, realizado en conjunto con MICCAI 2020, en Lima, Perú, en octubre de 2020. El taller se llevó a cabo de manera virtual debido a la pandemia de COVID-19. Los 17 artículos completos y 2 artículos breves presentados en este volumen fueron cuidadosamente revisados y seleccionados para su inclusión en este libro. Las contribuciones describen nuevos modelos y métodos predictivos de vanguardia que resuelven problemas desafiantes en el campo médico para una medicina predictiva de alta precisión. Nota de contenido: Context-Aware Synergetic Multiplex Network for Multi-Organ Segmentation of Cervical Cancer MRI -- Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation -- Adversarial Brain Multiplex Prediction From a Single Network for High-Order Connectional Gender-Specific Brain Mapping -- Learned deep radiomics for survival analysis with attention -- Robustification of Segmentation Models Against Adversarial Perturbations In Medical Imaging -- Joint Clinical Data and CT Image based Prognosis: A Case Study on Postoperative Pulmonary Venous Obstruction Prediction -- Low-Dose CT Denoising using Octave Convolution with High and Low Frequency bands -- Conditional Generative Adversarial Network for Predicting 3D Medical Images Affected by Alzheimer's Diseases -- Inpainting Cropped Diffusion MRI using Deep Generative Models -- Multi-View Brain HyperConnectome AutoEncoder For Brain State Classification -- Foreseeing Brain Graph EvolutionOver Time Using Deep Adversarial Network Normalizer -- Longitudinal prediction of anatomical changes of parotid glands -- Deep Parametric Mixtures for Modeling the Functional Connectome -- Deep EvoGraphNet Architecture For Time-Dependent Brain Graph Data Synthesis From a Single Timepoint -- Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Prediction -- mr2 NST: Multi-Resolution and Multi-Reference Neural Style Transfer for Mammography -- Template-oriented Multi-task Sparse Low-rank Learning for Parkinson's Diseases Diagnosis -- Multimodal Prediction of Breast Cancer Relapse Prior to Neoadjuvant Chemotherapy Treatment. En línea: https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Link: https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i Predictive Intelligence in Medicine : Third International Workshop, PRIME 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings [documento electrónico] / Rekik, Islem, ; Adeli, Ehsan, ; Park, Sang Hyun, ; Valdés Hernández, Maria del C., . - 1 ed. . - [s.l.] : Springer, 2020 . - XII, 212 p. 65 ilustraciones.
ISBN : 978-3-030-59354-4
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Palabras clave: Ingeniería Informática y Redes Visión Entornos informáticos Red informática Inteligencia artificial Visión por computador Procesamiento de imágenes Ordenador Ingeniería Informática Aplicaciones informáticas y de sistemas de información Índice Dewey: 006.3 Inteligencia artificial Resumen: Este libro constituye las actas del Tercer Taller Internacional sobre Inteligencia Predictiva en Medicina, PRIME 2020, realizado en conjunto con MICCAI 2020, en Lima, Perú, en octubre de 2020. El taller se llevó a cabo de manera virtual debido a la pandemia de COVID-19. Los 17 artículos completos y 2 artículos breves presentados en este volumen fueron cuidadosamente revisados y seleccionados para su inclusión en este libro. Las contribuciones describen nuevos modelos y métodos predictivos de vanguardia que resuelven problemas desafiantes en el campo médico para una medicina predictiva de alta precisión. Nota de contenido: Context-Aware Synergetic Multiplex Network for Multi-Organ Segmentation of Cervical Cancer MRI -- Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation -- Adversarial Brain Multiplex Prediction From a Single Network for High-Order Connectional Gender-Specific Brain Mapping -- Learned deep radiomics for survival analysis with attention -- Robustification of Segmentation Models Against Adversarial Perturbations In Medical Imaging -- Joint Clinical Data and CT Image based Prognosis: A Case Study on Postoperative Pulmonary Venous Obstruction Prediction -- Low-Dose CT Denoising using Octave Convolution with High and Low Frequency bands -- Conditional Generative Adversarial Network for Predicting 3D Medical Images Affected by Alzheimer's Diseases -- Inpainting Cropped Diffusion MRI using Deep Generative Models -- Multi-View Brain HyperConnectome AutoEncoder For Brain State Classification -- Foreseeing Brain Graph EvolutionOver Time Using Deep Adversarial Network Normalizer -- Longitudinal prediction of anatomical changes of parotid glands -- Deep Parametric Mixtures for Modeling the Functional Connectome -- Deep EvoGraphNet Architecture For Time-Dependent Brain Graph Data Synthesis From a Single Timepoint -- Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Prediction -- mr2 NST: Multi-Resolution and Multi-Reference Neural Style Transfer for Mammography -- Template-oriented Multi-task Sparse Low-rank Learning for Parkinson's Diseases Diagnosis -- Multimodal Prediction of Breast Cancer Relapse Prior to Neoadjuvant Chemotherapy Treatment. En línea: https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Link: https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i
