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Jiashu Chen

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YNICL Journal 2023 Journal Article

A presurgical voxel-wise predictive model for cerebellar mutism syndrome in children with posterior fossa tumors

  • Wei Yang
  • Yiming Li
  • Zesheng Ying
  • Yingjie Cai
  • Xiaojiao Peng
  • HaiLang Sun
  • Jiashu Chen
  • Kaiyi Zhu

BACKGROUND: This study aimed to investigate cerebellar mutism syndrome (CMS)-related voxels and build a voxel-wise predictive model for CMS. METHODS: From July 2013 to January 2022, 188 pediatric patients diagnosed with posterior fossa tumor were included in this study, including 38 from a prospective cohort recruited between 2020 and January 2022, and the remaining from a retrospective cohort recruited in July 2013-Aug 2020. The retrospective cohort was divided into the training and validation sets; the prospective cohort served as a prospective validation set. Voxel-based lesion symptoms were assessed to identify voxels related to CMS, and a predictive model was constructed and tested in the validation and prospective validation sets. RESULTS: No significant differences were detected among these three data sets in CMS rate, gender, age, tumor size, tumor consistency, presence of hydrocephalus and paraventricular edema. Voxels related to CMS were mainly located in bilateral superior and inferior cerebellar peduncles and the superior part of the cerebellum. The areas under the curves for the model in the training, validation and prospective validation sets were 0.889, 0.784 and 0.791, respectively. CONCLUSIONS: Superior and inferior cerebellar peduncles and the superior part of the cerebellum were related to CMS, especially the right side, and voxel-based lesion-symptom analysis could provide valuable predictive information before surgery.

AAMAS Conference 2016 Conference Paper

Egalitarianism of Random Assignment Mechanisms (Extended Abstract)

  • Haris Aziz
  • Aris Filos-Ratsikas
  • Jiashu Chen
  • Simon Mackenzie
  • Nicholas Mattei

We consider the egalitarian welfare of random assignment mechanisms when agents have unrestricted cardinal utilities over the objects. We define and give bounds on how well different random assignment mechanisms approximate the optimal egalitarian value (OEV) and investigate the effect that different well-known properties like ordinality, envyfreeness, and truthfulness have on the achievable egalitarian value. Finally, we conduct detailed experiments analyzing the tradeoffs between efficiency with envy-freeness or truthfulness using two prominent random assignment mechanisms — random serial dictatorship and the probabilistic serial mechanism — for different classes of utility functions and distributions.

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