From 1c8c3cda2db835771e9e793f31b38022002ae0ae Mon Sep 17 00:00:00 2001 From: Kyle Belanger Date: Tue, 20 Jun 2023 17:02:03 -0400 Subject: [PATCH] Update chapter5.qmd --- chapter5.qmd | 19 ++++++++----------- 1 file changed, 8 insertions(+), 11 deletions(-) diff --git a/chapter5.qmd b/chapter5.qmd index 78247c2..79d27c3 100644 --- a/chapter5.qmd +++ b/chapter5.qmd @@ -54,15 +54,11 @@ As Rabbani et al. study showed, Machine Learning in the Clinical Laboratory is an emerging field. However, few existing studies relate to predicting laboratory values based on other results [-@rabbani2022]. The few studies that do exist follow a similar premise. All are trying to -reduce redundant laboratory testing and thus lower the cost burden on -the patient. +reduce redundant laboratory testing, thus lowering the patient's cost +burden. ## Study Limitations -Section overview - In progress - -### MIMIC Database - While the MIMIC-IV database allowed for a first run of the study, it does suffer from some issues compared to other patient results. The MIMIC-IV database only contains results from ICU patients. Thus the @@ -95,11 +91,12 @@ adjustment, race explaining 6.5 percent of the variation in TSH levels included in developing a future algorithm. However, as it stands, the current data set has incomplete data for patient race and ethnicity. -### Other Limitations +As Machine learning algorithms become more and more powerful, it is +additionally important from an infrastructure standpoint to have the +processing power capable of handling the algorithms. This becomes even +more important in an attempt to put the algorithm into practice, as the +computer must be able to process results in mere milliseconds. -Should I write about my computer? - It is not capable of running the -more powerful algorithm - -### Future Studies +## Future Studies Explain how to fix these issues.