Most importantly, matching cancer registration and HES data also allows the identification of surgeons and hospitals for each type of treatment if these data have not been collected by the cancer registry, thus increasing the number of cases that can be returned to surgeons for checking.
In this case, it can be checked that m∗ can be found as follows: m ∗ = max m ∈ { 1, 2, …, n T } : 1 γ m · ∑ i = 1 m 1 γ i - ∑ i = 1 m 1 γ i < P. If the modal matrices of R R and S R are the same, I T = I and I R = I, then the optimal training is given by [9], as these assumptions correspond to the problem solved therein.
Then considering all possible cases, it can be checked that, for all (m,n,pin X), we have D m,n leqfrac{7}{2}bigl[D m,p +D p,n bigr].
Then considering all possible cases, it can be checked that for all m, n, p ∈ X, we have d ( m, p ) ≤ 5 2 ( d ( m, n ) + d ( n, p ) ).
By a careful calculation (there are 21 nontrivial cases) it can be checked that condition (3.2) (i.e., condition (3.3)) is satisfied for all X, S ∈ X 2. Hence, Theorem 2 can be applied to conclude that f has a coupled fixed point (which is ( 0, 0,) ).
