Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information.

Journal: Asian Pacific journal of cancer prevention : APJCP

PMID: 32856859

Abstract

PURPOSE: To evaluate the robustness of multiple machine learning classifiers for breast cancer risk estimation in the presence of incomplete or inaccurate information.

Authors

Siva Teja Kakileti

Niramai Health Analytix Pvt Ltd., Koramangala, Bangalore, Karnataka, India.
Geetha Manjunath

Niramai Health Analytix Pvt Ltd., Koramangala, Bangalore, Karnataka, India.
Andre Dekker

Department of Radiation Oncology (MAASTRO Clinic), Dr. Tanslaan 12, Maastricht, The Netherlands.
Leonard Wee

Maastricht University Medical Centre, Netherlands.

Keywords

Adult Aged Aged, 80 and over Breast Neoplasms Data Interpretation, Statistical Female Follow-Up Studies Humans Incidence Machine Learning Middle Aged Neural Networks, Computer Prognosis ROC Curve United States

External Resources

View on PubMed Access via DOI PubMed (32856859)

Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information.

Abstract

Authors

Keywords

External Resources

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