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2nd PRIME@MICCAI 2019: Shenzhen, China
- 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. Lecture Notes in Computer Science 11843, Springer 2019, ISBN 978-3-030-32280-9 - Razvan V. Marinescu
, Neil P. Oxtoby, Alexandra L. Young, Esther E. Bron
TADPOLE Challenge: Accurate Alzheimer's Disease Prediction Through Crowdsourced Forecasting of Future Data. 1-10 - Alina Giger
Inter-fractional Respiratory Motion Modelling from Abdominal Ultrasound: A Feasibility Study. 11-22 - Ahmed M. Anter
Adaptive Neuro-Fuzzy Inference System-Based Chaotic Swarm Intelligence Hybrid Model for Recognition of Mild Cognitive Impairment from Resting-State fMRI. 23-33 - Chiyu Feng, Lili Jin, Chuangyong Xu, Peng Yang, Tianfu Wang, Baiying Lei
Deep Learning via Fused Bidirectional Attention Stacked Long Short-Term Memory for Obsessive-Compulsive Disorder Diagnosis and Risk Screening. 34-43 - Antoine Rivail, Ursula Schmidt-Erfurth, Wolf-Dieter Vogl, Sebastian M. Waldstein, Sophie Riedl, Christoph Grechenig, Zhichao Wu, Hrvoje Bogunovic:
Modeling Disease Progression in Retinal OCTs with Longitudinal Self-supervised Learning. 44-52 - Kevin P. Nguyen
Predicting Response to the Antidepressant Bupropion Using Pretreatment fMRI. 53-62 - Olfa Ghribi, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik:
Progressive Infant Brain Connectivity Evolution Prediction from Neonatal MRI Using Bidirectionally Supervised Sample Selection. 63-72 - Alexander Katzmann
Computed Tomography Image-Based Deep Survival Regression for Metastatic Colorectal Cancer Using a Non-proportional Hazards Model. 73-80 - Mayssa Soussia, Islem Rekik:
7 Years of Developing Seed Techniques for Alzheimer's Disease Diagnosis Using Brain Image and Connectivity Data Largely Bypassed Prediction for Prognosis. 81-93 - Milad Ahmadi, Mohammad Sabokrou, Mahmood Fathy
Generative Adversarial Irregularity Detection in Mammography Images. 94-104 - Alaa Bessadok
Hierarchical Adversarial Connectomic Domain Alignment for Target Brain Graph Prediction and Classification from a Source Graph. 105-114 - Kübra Cengiz, Islem Rekik:
Predicting High-Resolution Brain Networks Using Hierarchically Embedded and Aligned Multi-resolution Neighborhoods. 115-124 - Ihsan Ullah, Philip Chikontwe, Sang Hyun Park:
Catheter Synthesis in X-Ray Fluoroscopy with Generative Adversarial Networks. 125-133 - Aojie Li, Ling Yue, Manhua Liu, Shifu Xiao:
Prediction of Clinical Scores for Subjective Cognitive Decline and Mild Cognitive Impairment. 134-141 - Haijun Lei, Hancong Li, Ahmed Elazab
Diagnosis of Parkinson's Disease in Genetic Cohort Patients via Stage-Wise Hierarchical Deep Polynomial Ensemble Learning. 142-150 - Robert Holland, Uday Patel, Phillip Lung, Elisa Chotzoglou, Bernhard Kainz
Automatic Detection of Bowel Disease with Residual Networks. 151-159 - Qifan Yang, Sophia I. Thomopoulos, Linda Ding, Wesley Surento, Paul M. Thompson
Support Vector Based Autoregressive Mixed Models of Longitudinal Brain Changes and Corresponding Genetics in Alzheimer's Disease. 160-167 - Hansang Lee, Helen Hong, Jinsil Seong, Jin Sung Kim, Junmo Kim:
Treatment Response Prediction of Hepatocellular Carcinoma Patients from Abdominal CT Images with Deep Convolutional Neural Networks. 168-176
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