自闭症谱系障碍轨迹的跨语料库无监督学习

IF 4.3 3区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Journal of Machine Learning Research Pub Date : 2016-01-01 DOI:10.5555/2946645.3007086

ElibolHuseyin Melih, NguyenVincent, LindermanScott, JohnsonMatthew, HashmiAmna, Doshi-VelezFinale

引用次数: 0

摘要

患有发育障碍的患者，如自闭症谱系障碍(ASD)，即使命名的诊断仍然固定，其症状也会随着时间而变化。例如，有语言障碍的人……

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Cross-corpora unsupervised learning of trajectories in autism spectrum disorders

Patients with developmental disorders, such as autism spectrum disorder (ASD), present with symptoms that change with time even if the named diagnosis remains fixed. For example, language impairmen...

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来源期刊

Journal of Machine Learning Research 工程技术-计算机：人工智能

CiteScore

18.80

自引率

0.00%

发文量

审稿时长

3 months

期刊介绍： The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing. JMLR seeks previously unpublished papers on machine learning that contain: new principled algorithms with sound empirical validation, and with justification of theoretical, psychological, or biological nature; experimental and/or theoretical studies yielding new insight into the design and behavior of learning in intelligent systems; accounts of applications of existing techniques that shed light on the strengths and weaknesses of the methods; formalization of new learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks; development of new analytical frameworks that advance theoretical studies of practical learning methods; computational models of data from natural learning systems at the behavioral or neural level; or extremely well-written surveys of existing work.