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PROPOSAL FOR A METHODOLOGY FOR THE EARLY CLASSIFICATION OF THE POPULATION AT RISK OF CANCER

Principal Investigator
Name
Carlos Andres Munoz Pineda
Degrees
M.D.
Institution
Universidad Internacional de la Rioja
Position Title
Student
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-1403
Initial CDAS Request Approval
Dec 4, 2023
Title
PROPOSAL FOR A METHODOLOGY FOR THE EARLY CLASSIFICATION OF THE POPULATION AT RISK OF CANCER
Summary
The proposed methodology is based on machine learning techniques and aims to identify patterns of exposure to cancer risk factors in a population. The work also presents the results obtained with the algorithm and concludes with reflections on its applicability and utility for the National Observatory of Cancer in Colombia
Aims

• To develop and document an early classification model of the population at risk of cancer using the Naive Bayesian supervised learning algorithm. This involves building and optimizing the model, as well as validating it through independent test data.
• Propose a methodology that allows the integration of the developed model in a process of early detection of the disease, in the context of the National Cancer Observatory in Colombia.

Collaborators

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