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BrainNET: Inference of Brain Network Topology Using Machine Learning
Brain Connectivity ( IF 3.4 ) Pub Date : 2020-10-19 , DOI: 10.1089/brain.2020.0745 Gowtham Krishnan Murugesan 1 , Chandan Ganesh 1 , Sahil Nalawade 1 , Elizabeth M Davenport 1 , Ben Wagner 1 , Won Hwa Kim 2 , Joseph A Maldjian 1
Brain Connectivity ( IF 3.4 ) Pub Date : 2020-10-19 , DOI: 10.1089/brain.2020.0745 Gowtham Krishnan Murugesan 1 , Chandan Ganesh 1 , Sahil Nalawade 1 , Elizabeth M Davenport 1 , Ben Wagner 1 , Won Hwa Kim 2 , Joseph A Maldjian 1
Affiliation
Background: To develop a new functional magnetic resonance image (fMRI) network inference method, BrainNET, that utilizes an efficient machine learning algorithm to quantify contributions of various regions of interests (ROIs) in the brain to a specific ROI.
中文翻译:
BrainNET:使用机器学习推断脑网络拓扑
背景:为了开发一种新的功能磁共振图像 (fMRI) 网络推理方法 BrainNET,该方法利用高效的机器学习算法来量化大脑中各个感兴趣区域 (ROI) 对特定 ROI 的贡献。
更新日期:2020-10-30
中文翻译:
BrainNET:使用机器学习推断脑网络拓扑
背景:为了开发一种新的功能磁共振图像 (fMRI) 网络推理方法 BrainNET,该方法利用高效的机器学习算法来量化大脑中各个感兴趣区域 (ROI) 对特定 ROI 的贡献。