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Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study (Preprint)

机译：无监督机器学习，用于识别挑战行为型材，以探索自闭症谱系疾病儿童的基于群体的治疗疗效：回顾性数据分析研究（预印）

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Julie Gardner-Hoag; Marlena Novack; Chelsea Parlett-Pelleriti; Elizabeth Stevens; Dennis Dixon; Erik Linstead;
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1. Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study [J] . Julie Gardner-Hoag, Marlena Novack, Chelsea Parlett-Pelleriti, JMIR Medical Informatics . 2021,第6期

机译：无监督机器学习，用于识别挑战行为型材，以探索自闭症谱系紊乱儿童的基于群体的治疗疗效：回顾性数据分析研究
2. Progression of challenging behaviors in children and adolescents with Autism Spectrum Disorders as measured by the Autism Spectrum Disorders-Problem Behaviors for Children (ASD-PBC) [J] . Johnny L Matson, Sara Mahan, Julie A. Hess, Research in autism spectrum disorders . 2010,第3期

机译：通过自闭症谱系障碍-儿童问题行为（ASD-PBC）衡量的自闭症谱系障碍的儿童和青少年中挑战性行为的进展
3. Identification and analysis of behavioral phenotypes in autism spectrum disorder via unsupervised machine learning [J] . Stevens Elizabeth, Dixon Dennis R., Novack Marlena N., International journal of medical informatics . 2019,第SEPa期

机译：通过无监督机器学习识别和分析自闭症谱系障碍的行为表型
4. A Speech Emotion Recognition Solution-based on Support Vector Machine for Children with Autism Spectrum Disorder to Help Identify Human Emotions [C] . Rezwan Matin, Damian Valles Conference on Intermountain Engineering, Technology and Computing . 2020

机译：基于支持向量机的自闭症谱系障碍儿童语音情感识别解决方案，用于识别人类情感
5. Exploring the Impact of Challenging Behaviors on Treatment Efficacy in Autism Spectrum Disorder [D] . Gardner-Hoag, Juliana. 2019

机译：挑战性行为对自闭症谱系治疗疗效的影响
6. Development of the parental self-efficacy scale for preventing challenging behaviors in children with autism spectrum disorder [O] . Yuri Kabashima, Etsuko Tadaka, Azusa Arimoto 2020

机译：父母自我疗效规模的发展防止自闭症谱系障碍儿童挑战性行为
7. Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study [O] . Julie Gardner-Hoag, Marlena Novack, Chelsea Parlett-Pelleriti, 2021

机译：识别挑战行为概况的无监督机器学习，以探索自闭症谱系疾病儿童的基于群体的治疗疗效：回顾性数据分析研究

Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study (Preprint)

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