pima_diabetes

A dataset containing diabetes status and other health-related variables for
768 females, at least 21 years old, of Pima Indian heritage. As pointed out
(see source URL below), the source data had some biologically impossible zero
values. We have replaced zero values in every variable except
<code>Pregnancies</code> with NA.

datasets

Aims to make machine learning in healthcare as easy as possible.
You can develop customized, reliable, high-performance machine learning models with minimal code.
Models are created with automatic preprocessing, hyperparameter tuning, and
algorithm selection (between
'xgboost' Chen, T. & Guestrin, C. (2016) <arXiv:1603.02754>,
'ranger' Wright, M. N., & Ziegler, A. (2017) <doi:10.18637/jss.v077.i01>,
and 'glm' Friedman J, Hastie T, Tibshirani R. (2010) <doi:10.18637/jss.v033.i01>)
so that they can be easily
put into production. Additionally, there are tools to help understand how a model makes its
predictions, select prediction threshholds for operational use, and evaluate model performance over time.
Code uses 'tidyverse' syntax and most methods have an associated visualization.

Mike Mastanduno

healthcareai

Tools for Healthcare Machine Learning

Levi Thatcher

Michael Levy

Taylor Larsen

Taylor Miller

Rex Sumsion

pima_diabetes function

A tibble data frame with 768 rows and 10 variables:<dl>
 <dt>patient_id</dt>
<dd>Unique identifier</dd> <dt>pregnancies</dt>
<dd>Number of times pregnant</dd> <dt>plasma_glucose</dt>
<dd>Plasma glucose concentration 2 hours in an oral
 glucose tolerance test</dd> <dt>diastolic_bp</dt>
<dd>Diastolic blood pressure (mm Hg)</dd> <dt>skinfold</dt>
<dd>Triceps skin fold thickness (mm)</dd> <dt>insulin</dt>
<dd>2-Hour serum insulin (mu U/ml)</dd> <dt>weight_class</dt>
<dd>Derived from BMI</dd> <dt>pedigree</dt>
<dd>Diabetes pedigree function</dd> <dt>age</dt>
<dd>Age (years)</dd> <dt>diabetes</dt>
<dd>Y/N diagnosis per WHO criteria</dd>
</dl>

Format

Patient diabetes dataset — pima_diabetes

A tibble data frame with 768 rows and 10 variables:<dl>
 <dt>patient_id</dt>
<dd>Unique identifier</dd>

 <dt>pregnancies</dt>
<dd>Number of times pregnant</dd>

 <dt>plasma_glucose</dt>
<dd>Plasma glucose concentration 2 hours in an oral
 glucose tolerance test</dd>

 <dt>diastolic_bp</dt>
<dd>Diastolic blood pressure (mm Hg)</dd>

 <dt>skinfold</dt>
<dd>Triceps skin fold thickness (mm)</dd>

 <dt>insulin</dt>
<dd>2-Hour serum insulin (mu U/ml)</dd>

 <dt>weight_class</dt>
<dd>Derived from BMI</dd>

 <dt>pedigree</dt>
<dd>Diabetes pedigree function</dd>

 <dt>age</dt>
<dd>Age (years)</dd>

 <dt>diabetes</dt>
<dd>Y/N diagnosis per WHO criteria</dd>


</dl>

pima_diabetes: Patient diabetes dataset

Description

Usage

Arguments

Format

See Also