Building a Binary Classification Machine-Learning Model: A Guide to Predicting Participation in a Lyme Disease Program at a Medical Institute.

The field of data analysis, preparation, and machine learning is rapidly expanding, offering numerous libraries and resources for exploration. Researchers gain knowledge through various channels, but few resources provide a comprehensive framework for building machine-learning models. We present a step-by-step framework for constructing a robust Random Forest classification model to fill this gap.

Cancer incidence and mortality in children in the Mexican Social Security Institute (1996-2013).

Objective: To identify the cancer incidence and mortality in Mexican Social Security Institute beneficiary (MSSI-B) children during 1996-2013.

Materials And Methods: Both cancer cases (n=4 728) and deaths (n=2 378) were analyzed in MSSI-B children who were registered in five states of the Mexican Republic. The incidence and mortality trends and the incidences (rate x 1 000 000 children / year) of the type of cancer, age, sex, and place of residence were obtained.