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