Heterogeneous Data Fusion to Type Brain Tumor Biopsies

机译：异构数据融合以类型脑肿瘤活检。

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Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontology. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. In this paper, we use machine learning algorithms to create a novel framework to perform the heterogeneous data fusion on both metabolic and molecular datasets, including state-of-the-art high-resolution magic angle spinning (HRMAS) proton (1H) Magnetic Resonance Spectroscopy and gene transcriptome profiling, to intact brain tumor biopsies and to identify different profiles of brain tumors. Our experimental results show our novel framework outperforms any analysis using individual dataset.

机译：生物医学信息学的当前研究涉及多个异类数据集的分析。这包括患者人口统计学，临床和病理数据，治疗史，患者预后以及基因表达，DNA序列和其他信息来源，例如基因本体论。这些数据集的分析可以导致更好的疾病诊断，预后，治疗和药物发现。在本文中，我们使用机器学习算法创建了一个新颖的框架，以对代谢数据集和分子数据集执行异类数据融合，包括最新的高分辨率魔角旋转（HRMAS）质子（1H）磁共振光谱学和基因转录组分析，以完整的脑肿瘤活组织检查并鉴定脑肿瘤的不同特征。我们的实验结果表明，我们的新颖框架优于使用单个数据集进行的任何分析。

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《Artificial intelligence applications and innovations III》|2009年|233-240|共8页
会议地点 Thessaloniki(GR);Thessaloniki(GR)
作者
Vangelis Metsis; Heng Huang; Fillia Makedon; Aria Tzika;
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作者单位

University of Texas at Arlington, USA;

University of Texas at Arlington, USA;

University of Texas at Arlington, USA;

NMR Surgical Laboratory, Department of Surgery, Harvard Medical School and Massachusetts General Hospital, Boston, USA;

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原文格式 PDF
正文语种 eng
中图分类人工智能理论;
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专利

1. Heterogeneous data fusion for brain tumor classification [J] . MetsisV., HuangH., AndronesiO.C., Oncology reports . 2012,第4期

机译：异构数据融合用于脑肿瘤分类
2. Multiplanar MRI-CT fusion neuronavigation-guided serial stereotactic biopsy of human brain tumors: proof of a strong correlation between tumor imaging and histopathology by a new technical approach. [J] . Kuhn SA, Romeike B, Walter J Journal of Cancer Research and Clinical Oncology . 2009,第9期

机译：人脑肿瘤的多平面MRI-CT融合神经导航引导的连续立体定位活检：通过一种新的技术方法证明了肿瘤成像与组织病理学之间的密切相关性。
3. Preuss Resident Research Award: maximal resection of low-grade intrinsic brain tumors using "awake" craniotomy and multiple marginal smear biopsies: neurological deficit rate and long-term survival data. [J] . Murphy M, Dinsmore J, Wilkins PR, Clinical neurosurgery. . 2006,第0期

机译：Preuss居民研究奖：使用“清醒”颅骨切开术和多次边缘涂片活检术可最大程度切除低度内在性脑部肿瘤：神经功能缺损率和长期生存数据。
4. Heterogeneous Data Fusion to Type Brain Tumor Biopsies [C] . IFIP conference on artificial intelligence applications and innovations . 2009

机译：异质数据融合到脑肿瘤活检
5. Novel Statistical Learning Methods for Multi-modality Heterogeneous Data Fusion in Health Care Applications [D] . Liu, Xiaonan 2019

机译：卫生保健应用中多模式异构数据融合的新型统计学习方法
6. Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources [O] . Sebastian Neubert, André Geißler, Thomas Roddelkopf, 2019

机译：面向数据科学的预防性健康管理系统的多传感器融合方法：异构数据源的分散数据收集方法的概念和发展
7. Heterogeneous Data Fusion to Type Brain Tumor Biopsies [O] . Vangelis Metsis, Heng Huang, Fillia Makedon, 2009

机译：异质数据融合到脑肿瘤活检

Heterogeneous Data Fusion to Type Brain Tumor Biopsies

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