Beschreibung
Laboratory test results play a significant role in clinical decisions for individual patients. Analysing these results over large populations and extended periods could offer additional insights. The UKE has collected lab results for 24 years, and hundreds of thousands of patients; however, this wealth of data has yet to be explored. Decomposing the factors that contribute to the observed variance beyond the specifics of the individual case presents a formidable task. Data science techniques are essential in identifying long-term trends and technical discontinuities on top of circadian and seasonal variations so that reference ranges, which allow for tagging cases outside the typical variance, can be determined from the data itself.
Keywords
Clinical Lab Data
(Partial) Autocorrelation
Reference Limit Estimator
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