基于钙特征的随机森林模型脑肿瘤诊断平台

IF 5.3 2区 医学 Q1 ENGINEERING, BIOMEDICAL Biocybernetics and Biomedical Engineering Pub Date : 2024-04-01 DOI:10.1016/j.bbe.2024.07.002
Ziyi Qiu , Xiaoping Hu , Ting Xu , Kai Sheng , Guanlin Lu , Xiaona Cao , Weicheng Lu , Jingdun Xie , Bingzhe Xu
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引用次数: 0

摘要

钙通量已被成功证实在脑肿瘤的恶性增殖和进展中发挥重要作用,可作为重要的诊断指南。然而,由于钙信号具有高度复杂性和异质性特征,基于钙信息的临床诊断仍具有挑战性。在此,我们利用随机森林分析框架提出了基于钙特征的肿瘤诊断和治疗指导平台(CA-TDT-GP),以有效预测复杂的肿瘤行为,为临床治疗提供指导。通过全面的特征重要性分析,筛选出与脑肿瘤生物学恶性相关的多个重要特征。它为了解脑肿瘤的生物学过程和选择药物提供了有用的指导。进一步的临床验证证实了该模型对肿瘤生物学特征的准确预测,同一队列患者的决定系数超过 0.86,新队列患者的决定系数超过 0.77。我们还进一步验证了该模型的临床恶性程度评估,其预测结果与确诊的 WHO 分级吻合率达 100%,这表明该平台在临床指导方面具有巨大潜力。这一前景广阔的模型为脑肿瘤研究和临床前治疗提供了一种新的诊断和治疗工具。
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Calcium feature-based brain tumor diagnosis platform using random forest model

Calcium flux has been successfully verified to play an important role in the malignant proliferation and progression of brain tumors, which can serve as an important diagnosis guide. However, clinical diagnosis based on calcium information remains challenging because of the highly complex and heterogeneous features in calcium signals. Here we propose a calcium feature-based tumor diagnosis and treatment guidance platform (CA-TDT-GP) using random forest analysis framework for the efficient prediction of complex tumor behaviors for clinical therapy guidance. Multiple important features associated with brain tumor biological malignancy were screened out through comprehensive feature importance analysis. It provided useful guidance for understanding the biological process and the selection of drugs of brain tumors. Further clinical validation confirmed the accurate prediction of tumor biological characteristics by the model, with a coefficient of determination of over 0.86 in the same cohort of patients and over 0.77 for the new cohort of patients. We further verified the clinical malignant assessment by this model, which performed a 100% prediction match with diagnosed WHO grades, indicating great potential of the platform for clinical guidance. This promising model provides a new diagnostic and therapeutic tool for brain tumor research and preclinical treatment.

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来源期刊
CiteScore
16.50
自引率
6.20%
发文量
77
审稿时长
38 days
期刊介绍: Biocybernetics and Biomedical Engineering is a quarterly journal, founded in 1981, devoted to publishing the results of original, innovative and creative research investigations in the field of Biocybernetics and biomedical engineering, which bridges mathematical, physical, chemical and engineering methods and technology to analyse physiological processes in living organisms as well as to develop methods, devices and systems used in biology and medicine, mainly in medical diagnosis, monitoring systems and therapy. The Journal''s mission is to advance scientific discovery into new or improved standards of care, and promotion a wide-ranging exchange between science and its application to humans.
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