= Joann G. Elmore
{c}
\b[Joann G. Elmore] is a <physician> whose research examines variability in cancer diagnosis, including how consistently <pathologists> classify <biopsy> material. Her research group's description connects that work with <statistics> and <machine learning> for evaluating diagnostic decisions.<Joann G. Elmore research group at UCLA>[“About Our Research Group”: cancer diagnosis, physician variability and statistical methods]{ref}
In a 2017 primary study, Elmore and colleagues assembled 240 skin <biopsy> cases and gave participating <pathologists> sets of 36 or 48 cases. The design included a second interpretation of the same cases at least eight months later; 187 <pathologists> completed 8,976 interpretations in the first phase. Comparing an observer with their own later reading, with other observers and with a reference panel answers three different questions about <statistical classification>.<Pathologists' diagnosis of invasive melanoma and melanocytic proliferations: observer accuracy and reproducibility study by Joann G. Elmore and others>[Abstract, Participants and Results; Methods, reference diagnoses; BMJ 357:j2813, DOI 10.1136/bmj.j2813]{ref}
The distinction is <within-observer agreement versus reference agreement>. In an illustrative set of 20 cases, an observer might repeat 18 of their earlier classifications but agree with a reference classification on only 14: the two proportions are $18/20=90\%$ and $14/20=70\%$. Repeating the same erroneous category increases the first proportion without improving the second. These are invented counts to explain the design, not results from Elmore's study. A consensus reference is an explicitly defined comparison standard; it does not make a panel infallible, and the diagnostic mix of a selected test set must be considered before interpreting an overall agreement percentage.
\Image[https://elmore.dgsom.ucla.edu/sites/default/files/styles/3_2_720x480/public/media/images/joann-elmore-resized.jpg.webp?h=f044ada5&itok=ll1d3WE4]
{title=Joann G. Elmore. UCLA research-group website, explicitly identified as a headshot of Dr. Elmore.}
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