Gholami Behnood, Norton Isaiah, Tannenbaum Allen R, Agar Nathalie Y R
Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:5258-61. doi: 10.1109/EMBC.2012.6347180.
The metabolism and composition of lipids is of increasing interest for understanding and detecting disease processes. Lipid signatures of tumor type and grade have been demonstrated using magnetic resonance spectroscopy. Clinical management and ultimate prognosis of brain tumors depend largely on the tumor type, subtype, and grade. Mass spectrometry, a well-known analytical technique used to identify molecules in a given sample based on their mass, can significantly improve the problem of tumor type classification. This work focuses on the problem of identifying lipid features to use as input for classification. Feature selection could result in improvements in classifier performance, discovery of biomarkers, improved data interpretation, and patient treatment.
脂质的代谢和组成对于理解和检测疾病过程越来越受到关注。利用磁共振波谱已证实了肿瘤类型和分级的脂质特征。脑肿瘤的临床管理和最终预后在很大程度上取决于肿瘤的类型、亚型和分级。质谱分析法是一种众所周知的分析技术，用于根据给定样本中分子的质量来识别分子，它可以显著改善肿瘤类型分类问题。这项工作聚焦于识别脂质特征作为分类输入的问题。特征选择可能会导致分类器性能的提高、生物标志物的发现、数据解释的改善以及患者治疗的优化。
