PPT-Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer’s Disease Analysis

Author : leah | Published Date : 2023-11-23

Junbo Ma Xiaofeng Zhu Defu Yang Jiazhou Chen Guorong Wu Graph Deep Learning for Medical Applications Sergei Voloboev TUM Motivation Motivation of the AD prediction

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "Attention-Guided Deep Graph Neural Netwo..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer’s Disease Analysis: Transcript

Junbo Ma Xiaofeng Zhu Defu Yang Jiazhou Chen Guorong Wu Graph Deep Learning for Medical Applications Sergei Voloboev TUM Motivation Motivation of the AD prediction Alzheimers disease AD is an irreversible progressive neurodegenerative disease. Professor Qiang Yang. Outline. Introduction. Supervised Learning. Convolutional Neural Network. Sequence Modelling: RNN and its extensions. Unsupervised Learning. Autoencoder. Stacked . Denoising. . Shuochao Yao, Yiwen Xu, Daniel Calzada. Network Compression and Speedup. 1. Source: . http://isca2016.eecs.umich.edu/. wp. -content/uploads/2016/07/4A-1.pdf. Network Compression and Speedup. 2. Why smaller models?. Deep Neural Networks . Huan Sun. Dept. of Computer Science, UCSB. March 12. th. , 2012. Major Area Examination. Committee. Prof. . Xifeng. . Yan. Prof. . Linda . Petzold. Prof. . Ambuj. Singh. Andy Saykin. WW-ADNI Meeting. London, UK. July 14, 2017. asaykin@iupui.edu. Overview and 2017 Updates. ADNI-3 sample collection (banked at NCRAD). Longitudinal DNA & RNA (12 new, 79 continuing). Changes in ADNI-3 include PBMC and RBC collection. Deep . Learning. James K . Baker, Bhiksha Raj. , Rita Singh. Opportunities in Machine Learning. Great . advances are being made in machine learning. Artificial Intelligence. Machine. Learning. After decades of intermittent progress, some applications are beginning to demonstrate human-level performance!. Weifeng Li, . Victor Benjamin, Xiao . Liu, and . Hsinchun . Chen. University of Arizona. 1. Acknowledgements. Many of the pictures, results, and other materials are taken from:. Aarti. Singh, Carnegie Mellon University. Eye-height and Eye-width Estimation Method. Daehwan Lho. Advisor: Prof. . Joungho. Kim. TeraByte Interconnection and Package Laboratory. Department of Electrical Engineering . KAIST. Concept of the Proposed Fast and Accurate Deep . Lingxiao Ma. . †. , Zhi Yang. . †. , Youshan Miao. ‡. , Jilong Xue. ‡. , Ming Wu. ‡. , Lidong Zhou. ‡. , . Yafei. Dai. . †. †. . Peking University. ‡ . Microsoft Research. USENIX ATC ’19, Renton, WA, USA. classification from magnetic resonance. . brain images. RachnaJain. . NikitaJain. a. AkshayAggarwal. . D. JudeHemanth. Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering, New Delhi, . Topics: 1. st. lecture wrap-up, difficulty training deep networks,. image classification problem, using convolutions,. tricks to train deep networks . . Resources: http://www.cs.utah.edu/~rajeev/cs7960/notes/ . Mark Hasegawa-Johnson. April 6, 2020. License: CC-BY 4.0. You may remix or redistribute if you cite the source.. Outline. Why use more than one layer?. Biological inspiration. Representational power: the XOR function. Eli Gutin. MIT 15.S60. (adapted from 2016 course by Iain Dunning). Goals today. Go over basics of neural nets. Introduce . TensorFlow. Introduce . Deep Learning. Look at key applications. Practice coding in Python. Kannan . Neten. Dharan. Introduction . Alzheimer’s Disease is a kind of dementia which is caused by damage to nerve cells in the brain and the usual side effects of it are loss of memory or other cognitive impairments.. Erekle Shishniashvili. Seminar - Graph Deep Learning In Medical Imaging. Multi-head GAGNN: A Multi-head Guided Attention Graph Neural Network for Modeling . Spatio. -temporal Patterns of Holistic Brain Functional Networks.

Download Document

Here is the link to download the presentation.
"Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer’s Disease Analysis"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.