Conformal predictors in early diagnostics of ovarian and breast cancers
Conformal predictors in early diagnostics of ovarian and breast cancers
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DOI：
10.1007/s13748-012-0021-y
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发表时间：
2012-07
影响因子：
4.2
通讯作者：
Dmitry Devetyarov;I. Nouretdinov;Brian Burford;S. Camuzeaux;A. Gentry-Maharaj;A. Tiss;Celia J. Smith;Zhiyuan Luo;A. Chervonenkis;R. Hallett;V. Vovk;M. Waterfield;R. Cramer;J. Timms;J. Sinclair;U. Menon;I. Jacobs;A. Gammerman
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文献类型：
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作者：
Dmitry Devetyarov;I. Nouretdinov;Brian Burford;S. Camuzeaux;A. Gentry-Maharaj;A. Tiss;Celia J. Smith;Zhiyuan Luo;A. Chervonenkis;R. Hallett;V. Vovk;M. Waterfield;R. Cramer;J. Timms;J. Sinclair;U. Menon;I. Jacobs;A. Gammerman
这项工作描述了最近开发的一种名为蒙德里安预测器的机器学习技术在卵巢癌和乳腺癌风险评估中的应用。该分析基于在英国卵巢癌筛查合作试验中收集的人血清样本的质谱分析。这项工作描述了技术，并提出了分类（诊断）和相应的措施的诊断信心的结果。这种方法的主要优点是预测的有效性已得到证明。这项工作还描述了一种改善卵巢癌和乳腺癌早期诊断的方法，因为英国卵巢癌筛查合作试验中的数据是在7年内收集的，并且确实可以观察这段时间内人类血清的变化。统计学证实了改善的显著性（卵巢癌长达11个月，乳腺癌长达9个月）。此外，该方法使我们能够确定与先前检测到的相同的质谱峰，这些峰携带统计学上显著的信息，用于区分健康和患病患者。并对结果进行了讨论。
The work describes an application of a recently developed machine-learning technique called Mondrian predictors to risk assessment of ovarian and breast cancers. The analysis is based on mass spectrometry profiling of human serum samples that were collected in the United Kingdom Collaborative Trial of Ovarian Cancer Screening. The work describes the technique and presents the results of classification (diagnosis) and the corresponding measures of confidence of the diagnostics. The main advantage of this approach is a proven validity of prediction. The work also describes an approach to improve early diagnosis of ovarian and breast cancers since the data in the United Kingdom Collaborative Trial of Ovarian Cancer Screening were collected over a period of 7 years and do allow to make observations of changes in human serum over that period of time. Significance of improvement is confirmed statistically (for up to 11 months for ovarian cancer and 9 months for breast cancer). In addition, the methodology allowed us to pinpoint the same mass spectrometry peaks as previously detected as carrying statistically significant information for discrimination between healthy and diseased patients. The results are discussed.