updates

_quarto.yml

@@ -9,6 +9,8 @@ book:
     - index.qmd
     - chapter2.qmd
     - references.qmd
+  appendices:
+    - appendices/survey.qmd
 
 bibliography: references.bib
 csl: apa.csl

appendices/survey.qmd

@@ -0,0 +1,11 @@
+## Demographics
+
+What is your current role?
+
+Hospital Size?
+
+Annual Test Volume?
+
+## Features
+
+What is your current level of understanding of Machine Learning?

index.qmd

@@ -1 +1,43 @@
 # Introduction
+
+The primary business purpose of the clinical laboratory is to provide
+results of testing requested by physicians and other healthcare
+professionals. This testing in a broad sense is used to help solve
+diagnostic problems [@verboeket-vandevenne2012]. To continue to add
+value to the business purpose of the laboratory, laboratory
+professionals can add value beyond just running the provided tests.
+Laboratory professionals can add value through both reflective and
+reflex testing. Automated analyzers add most tests based on rules
+(algorithms) established by laboratory professionals; this is defined as
+'reflex testing.' Clinical biochemists add the remainder of tests after
+considering a more comprehensive range of information than can readily
+be incorporated into reflex testing algorithms; this is defined as
+'reflective testing' [@srivastava2010]. Both reflex and reflective
+testing became possible with the advent of laboratory information
+systems (LIS) that were sufficiently flexible to permit modification of
+existing test requests at various stages of the analytical process
+[@srivastava2010]. This research study will focus specifically on reflex
+testing, those tests added automatically by a set of rules established
+in each laboratory. In most current clinical laboratories, reflex
+testing is performed with a 'hard' cutoff, using a specifically
+established range with no means of flexibility [@murphy2021].
+
+<!--# Rewrite this section -->
+
+This study will examine the use of Machine learning to develop
+algorithms to allow flexibility for automatic reflex testing in clinical
+chemistry. The goal is to fill the gap between hard coded reflex testing
+and fully manual reflective testing using machine learning algorithms.
+
+<!--#  -->
+
+## Statement of Problem
+
+## Purpose and Research Question
+
+### Draft Question
+
+What are the beliefs, attitudes, opinions, and knowledge about machine
+learning in the clinical laboratory.
+
+## Significance

references.bib

@@ -0,0 +1,47 @@
+
+@article{verboeket-vandevenne2012,
+	title = {Reflective testing: adding value to laboratory testing},
+	author = {Verboeket-van de Venne, Wilhelmine P.H.G. and Aakre, Kristin M. and Watine, Joseph and Oosterhuis, Wytze P.},
+	year = {2012},
+	month = {07},
+	date = {2012-07-01},
+	journal = {Clinical Chemistry and Laboratory Medicine (CCLM)},
+	pages = {1249--1252},
+	volume = {50},
+	number = {7},
+	doi = {10.1515/cclm-2011-0611},
+	url = {https://www.degruyter.com/document/doi/10.1515/cclm-2011-0611/html},
+	langid = {en}
+}
+
+@article{srivastava2010,
+	title = {Reflex and reflective testing: efficiency and effectiveness of adding on laboratory tests},
+	author = {Srivastava, Rajeev and Bartlett, William A and Kennedy, Ian M and Hiney, Allan and Fletcher, Colin and Murphy, Michael J},
+	year = {2010},
+	month = {05},
+	date = {2010-05-01},
+	journal = {Annals of Clinical Biochemistry},
+	pages = {223--227},
+	volume = {47},
+	number = {3},
+	doi = {10.1258/acb.2010.009282},
+	url = {https://doi.org/10.1258/acb.2010.009282},
+	note = {Publisher: SAGE Publications},
+	langid = {en}
+}
+
+@article{murphy2021,
+	title = {Reflex and reflective testing: progress, but much still to be done},
+	author = {Murphy, Michael J},
+	year = {2021},
+	month = {03},
+	date = {2021-03},
+	journal = {Annals of Clinical Biochemistry},
+	pages = {75--77},
+	volume = {58},
+	number = {2},
+	doi = {10.1177/0004563221993153},
+	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7961679/},
+	note = {PMID: 33478239
+PMCID: PMC7961679}
+}