A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

Published:2014-04-29 Issue:4 Volume:9 Page:e95753
ISSN:1932-6203
Container-title:PLoS ONE
language:en
Short-container-title:PLoS ONE

Author:

Sweeney Elizabeth M.,Vogelstein Joshua T.,Cuzzocreo Jennifer L.,Calabresi Peter A.,Reich Daniel S.,Crainiceanu Ciprian M.,Shinohara Russell T.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference61 articles.

1. Machine learning for science: state of the art and future prospects;E Mjolsness;Science,2001

2. Machine learning for medical diagnosis: history, state of the art and perspective;I Kononenko;Artificial Intelligence in medicine,2001

3. Machine learning in bioinformatics;P Larrañaga;Briefings in bioinformatics,2006

4. An empirical comparison of voting classification algorithms: Bagging, boosting, and variants;E Bauer;Machine learning,1999

5. A preliminary performance comparison of five machine learning algorithms for practical ip traffic flow classification;N Williams;ACM SIGCOMM Computer Communication Review,2006

Cited by 37 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Individualized multi-modal MRI biomarkers predict 1-year clinical outcome in first-episode drug-naïve schizophrenia patients;Frontiers in Psychiatry;2024-09-13

2. Comparative analysis of alignment algorithms for macular optical coherence tomography imaging;International Journal of Retina and Vitreous;2023-10-02

3. How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review;NeuroImage: Clinical;2023

4. Neuroimaging in Machine Learning for Brain Disorders;Machine Learning for Brain Disorders;2023

5. An Enhanced Multiple Sclerosis Disease Diagnosis via an Ensemble Approach;Diagnostics;2022-07-21

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