Domain Adaptation and Generalization of Functional Medical Data: A Systematic Survey of Brain Data

Author:

Sarafraz Gita1ORCID,Behnamnia Armin1ORCID,Hosseinzadeh Mehran2ORCID,Balapour Ali2ORCID,Meghrazi Amin2ORCID,Rabiee Hamid R.2ORCID

Affiliation:

1. Computer Engineering, Sharif University of Technology, Tehran, Iran (the Islamic Republic of)

2. Computer Engineering, Sharif University of Technology, Tehran Iran (the Islamic Republic of)

Abstract

Despite the excellent capabilities of machine learning algorithms, their performance deteriorates when the distribution of test data differs from the distribution of training data. In medical data research, this problem is exacerbated by its connection to human health, expensive equipment, and meticulous setups. Consequently, achieving domain generalizations and domain adaptations under distribution shifts is an essential step in the analysis of medical data. As the first systematic review of domain generalization and domain adaptation on functional brain signals, the article discusses and categorizes various methods, tasks, and datasets in this field. Moreover, it discusses relevant directions for future research.

Funder

IR National Science Foundation

Publisher

Association for Computing Machinery (ACM)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3