Ziyi Qiu , Xiaoping Hu , Ting Xu , Kai Sheng , Guanlin Lu , Xiaona Cao , Weicheng Lu , Jingdun Xie , Bingzhe Xu
{"title":"Calcium feature-based brain tumor diagnosis platform using random forest model","authors":"Ziyi Qiu , Xiaoping Hu , Ting Xu , Kai Sheng , Guanlin Lu , Xiaona Cao , Weicheng Lu , Jingdun Xie , Bingzhe Xu","doi":"10.1016/j.bbe.2024.07.002","DOIUrl":null,"url":null,"abstract":"<div><p><span>Calcium flux<span> 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 </span></span>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.</p></div>","PeriodicalId":55381,"journal":{"name":"Biocybernetics and Biomedical Engineering","volume":"44 2","pages":"Pages 286-294"},"PeriodicalIF":5.3000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biocybernetics and Biomedical Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0208521624000494","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.