Article

Development and validation of a machine learning model to predict delays in seeking medical care among patients with breast cancer in China

2024-09-18

Abstract excerpt

<title>Abstract</title> <p>Background Delays in seeking medical care may affect the survival rates of breast cancer patients. We aimed to explore potential risk factors for the delay in seeking medical care among breast cancer patients by constructing a highly effective machine learning (ML) prediction model. Methods A cross-sectional methodology was utilized, and the demographic and clinical characteristics of...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6f9cc5b5-4c18-552d-889b-dee77e02abf3
DOI: 10.21203/rs.3.rs-4879410/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Development and validation of a machine learning model to predict delays in seeking medical care among patients with breast cancer in ChinaDOI 10.21203/rs.3.rs-4879410/v1Read

Deep Learning approach for breast cancer discovery Via gene correlationSemantic proximity Read

Factors Causing Delayed Presentations of Breast Cancer among Female patients in Sulaimaniyah Governorate, IraqSemantic proximity Read

Survival of Breast Cancer Patients and Associated Factors at the Douala General HospitalSemantic proximity Read

Predictive Modeling of Long-Term Survivors with Stage IV Breast Cancer Using the SEER-Medicare DatasetSemantic proximity Read

Modeling the Factors Associated with Mortality in Patients with Breast Cancer: A Machine Learning ApproachSemantic proximity Read

Modeling The Factors Associated with Mortality in Patients with Breast Cancer: A Machine Learning ApproachSemantic proximity Read

Database study of risk factors for breast cancer-related lymphedema: statistical analysis of 2359 cases in 10 yearsSemantic proximity Read

Machine Learning-based Predictive Model for Mortality in Female Breast Cancer Patients Considering Lifestyle FactorsSemantic proximity Read

Machine learning to construct an mRPS risk prognostic model for directing immunotherapy in patients with breast cancer based on the mCAF signature genesSemantic proximity Read

Improving the prognostic prediction accuracy on breast cancer patients through comprehensive machine survival modelsSemantic proximity Read

Development and validation of novel machine learning-based prognostic models and propensity score matching for comparison of surgical approaches in mucinous breast cancer: a multicenter studySemantic proximity Read

Machine learning prediction of pathological complete response and overall survival of breast cancer patients in an underserved inner-city populationSemantic proximity Read