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. 2022 Dec 28;13(1):95. doi: 10.3390/diagnostics13010095
Algorithm 1. Automatic prediction from the dataset.
input; dataset
output; prediction of attributes
for each disease data i
           for each attribute a
                     remove → a
                     for each disease data (i, t)
                                MIN = 0
                                for each disease data (i, k) & (k≠t)
                                          MIN = MIN + S (k, t)
                                          if (MIN < low_Thold)
                                                    low_Thold = MIN
                                          end if
                                end for
                      end for
                      for each disease data (i, t)
                                MAX = 0
                                for each disease data (i, k) & (k≠t)
                                          MAX = MAX + S (k, t)
                                                    if (MAX > high_Thold)
                                                              high_Thold = MAX
                                                              add → a
                                                              Ts = 0
                                                    end if
                                end for
                      end for
                      for each (i, t) & (a≠t)
                                Ts = Ts + S (a, t)
                      end for
                      if (Ts > high_Thold)
                                predict disease data (i, a)
                                else if (Ts > low_Thold)
                                          interpolated S = interpolate (Ts, low_Thold, high_Thold)
                      end if
                      if (interpolated S > cut-off)
                                predict disease data (i, a)
                      end if
            end for
end for