labs

A dataset containing 3,150 lab results for 96 unique synthetic patients.
 There are 6 unique labs, including platelets, serum creatinine,
 international normalized ratio (INR), white blood count (WBC), serum
 lactate, and serum bilirubin. Patient-level sampling rate, mean numeric
 value, standard deviation, and number of measurements per patient follow
 patterns observed in real electronic health record data. This dataset is
 included to demonstrate sepsis identification.

datasets

Examine any number of time series data frames to identify
instances in which various criteria are met within specified time
frames. In clinical medicine, these types of events are often
called "constellations of signs and symptoms", because a single
condition depends on a series of events occurring within a certain
amount of time of each other. This package was written to work with
any number of time series data frames and is optimized for speed
to work well with data frames with millions of rows.

Mark Sendak

constellation

Identify Event Sequences Using Time Series Joins

labs function

A data frame with 3150 rows and 4 variables:<dl class="dl-horizontal">
 <dt>PAT_ID</dt><dd>patient identification number, randomly generated integer</dd>
 <dt>RECORDED_TIME</dt><dd>recorded datetime of lab measurement, character</dd>
 <dt>VALUE</dt><dd>lab result value, numeric</dd>
 <dt>VARIABLE</dt><dd>categorical variable specifying the lab name, character</dd>
</dl>

Format

Synthesized lab results for cohort of 100 synthetic patients — labs

A data frame with 3150 rows and 4 variables:<dl class='dl-horizontal'>
 <dt>PAT_ID</dt><dd>patient identification number, randomly generated integer</dd>
 <dt>RECORDED_TIME</dt><dd>recorded datetime of lab measurement, character</dd>
 <dt>VALUE</dt><dd>lab result value, numeric</dd>
 <dt>VARIABLE</dt><dd>categorical variable specifying the lab name, character</dd>
</dl>

labs: Synthesized lab results for cohort of 100 synthetic patients

Description

Usage

Arguments

Format

Examples