We propose a breast cancer metastasis prediction model using a very small number of biologically interpretable features, and a simple yet novel model ...
We propose a breast cancer metastasis prediction model using a very small number of biologically interpretable features, and a simple yet novel model ...
Construction and evaluation of robust interpretation models for breast ...
ieeexplore.ieee.org › iel7
Here, we propose a breast cancer metastasis prediction model using a very small number of biologically interpretable features, and a simple yet novel model ...
Oct 18, 2021 · Interpretability of machine learning (ML) models represents the extent to which a model's decision-making process can be understood by model ...
Fingerprint. Dive into the research topics of 'Construction and Evaluation of Robust Interpretation Models for Breast Cancer Metastasis Prediction'.
A Robust Personalized Classification Method for Breast Cancer Metastasis Prediction · Deep Learning-Based Artificial Intelligence to Investigate Targeted ...
Construction and Evaluation of Robust Interpretation Models for Breast Cancer Metastasis Prediction. Nahim Adnan, Maryam Zand, Tim H.M. Huang, Jianhua Ruan.
People also ask
What predictive modeling is used for breast cancer?
What is the best prognostic indicator for breast cancer?
What are the six machine learning algorithms for breast cancer risk prediction?
What is the best evaluation metric for breast cancer detection?
Accurate prediction of breast cancer metastasis risks using gene expression data and machine learning can help improve cancer treatment and overall survival ...
The ease of use and faster time to results of the predictive model will eventually lead to the accurate and less-invasive prognosis for breast cancer patients.
Missing: Construction | Show results with:Construction
Ruan, "Construction and evaluation of robust interpretation models for breast cancer metastasis prediction," in IEEE/ACM Transactions on Computational ...