System and method for an automated clinical decision support system
A clinical decision support and automatic technology, applied in medical automated diagnosis, medical data mining, patient-specific data, etc., can solve problems such as insights without trade-offs, clinician importance ranking, etc.
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[0237] figure 1 Binarization methods for categorical and numerical variables are shown. Given the measured values, here eg values from measurements of creatinine levels or white blood cell levels, and one or more given thresholds (here two thresholds are used to create three ranges: low, normal and high), create binary variable. If the value lies in one of the intervals given by the threshold, "1" is applied, otherwise "0" is applied. exist figure 1 In the first row of , the measured creatinine value is above the upper threshold, which results in a "1" in the "Creatinine High" column. exist figure 1 In the first and second row of , the measured WBC value is between the upper and lower thresholds, which results in a "1" in the "WBC Normal" column.
[0238] figure 2 Various weighting functions in a sliding window are shown for modeling the temporal correlation of clinical events. The timeframe defined here (the length of the sliding window) is approximately 90 days. A...
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