kyle.belanger/DHSC-Capstone
1
0
Fork 0
Code Issues 1 Pull requests Projects Releases Packages Wiki Activity Actions

Update chapter3.qmd

Browse source
This commit is contained in:
Kyle Belanger 2023-01-13 08:11:42 -05:00
parent 42676db662
commit e64bb4a004
1 changed files with 16 additions and 2 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

18
chapter3.qmd
View file

@ -2,6 +2,20 @@
## Proposed Study Set Up
Using the Medical Information Mart for Intensive Care (MIMIC) IV Database develop and test a machine learning algorithm to determine if TSH reflex testing can be further reduced.
Using the Medical Information Mart for Intensive Care (MIMIC) IV
Database develop and test a machine learning algorithm to determine if
TSH reflex testing can be further reduced.
The MIMIC-IV database contains patient records from 2008 to 2019 for patients admitted to the critical care units of Beth Israel Deaconess Medical Center. It is a common database used for various studies. The data will be cleaned and tided to contain various patient demographics, and all available laboratory testing for each patient. The exact structure of the cleaned data will be determined later. Once cleaned the data will be split into a training and testing data set. The training data will be used to develop various machine learning algorithms to attempt to develop an algorithm that can perform better then the hard coded rules in place today. The study will primarily focus on TSH reflex testing as this is the most common reflex test used in most laboratories. The hypothesis however is that this model could be used for many different types of reflex testing in the lab.
The MIMIC-IV database contains patient records from 2008 to 2019 for
patients admitted to the critical care units of Beth Israel Deaconess
Medical Center. It is a common database used for various studies. The
data will be cleaned and tided to contain various patient demographics,
and all available laboratory testing for each patient. The exact
structure of the cleaned data will be determined later. Once cleaned the
data will be split into a training and testing data set. The training
data will be used to develop various machine learning algorithms to
attempt to develop an algorithm that can perform better then the hard
coded rules in place today. The study will primarily focus on TSH reflex
testing as this is the most common reflex test used in most
laboratories. The hypothesis however is that this model could be used
for many different types of reflex testing in the lab.