RAMAN SPECTROSCOPY FOR BREAST CANCER DETECTION VIA PRINCIPAL COMPONENT ANALYSIS

通过主成分分析进行乳腺癌检测拉曼光谱

• 批准号: 6314200
• 负责人: KAREN SHAFER
• 金额: $ 1.38万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-06-01 至 2001-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6314200
• 关键词: biomedical equipment development; biomedical resource; clinical research; female; human subject; human tissue; spectrometry; statistics /biometry; technology /technique; women's health

The goal of this research is to correlate Raman spectra with tissue pathology using principal component analysis. Principal component analysis enables us to reduce our data set into a smaller number of mathematical lineshapes, called principal components, which represent the spectral variations in the data. A linear combination of these principal components can then be used to fit individual data. Finally, logisitic regression is used to correlate fitting coefficients with disease classifications and develop a diagnostic algorithm. So far, we have developed an initial decision algorithm and are in the process of testing it on data not included in the original data set.

本研究的目的是将拉曼光谱与