Solving Bayes Theorem equation -> I can't calculate proper result I am solving questions for an edx course on Machine Learning.
One particular question is giving me a problem:

Assume a patient comes into the doctor’s office to test whether they have a particular disease.
The test is positive 85% of the time when tested on a patient with the disease (high sensitivity): 
P(test+|disease)=0.85
The test is negative 90% of the time when tested on a healthy patient (high specificity): 
P(test−|heathy)=0.90
The disease is prevalent in about 2% of the community: 
P(disease)=0.02
Using Bayes' theorem, calculate the probability that you have the disease if the test is positive.

My solution:

I have created a table

   sick   |   healthy
     2%   |   98%
+   90%   |   15%
-   10%   |   85%


From this I calculated bayes theorem like this:

                      (0,02*0,9)
P(A|B) = -----------------------------------------------------
               (0,02*0,9) + (0,15*0,98)


I get P(A|B)=0,109
however this answer is wrong,
where did I do mistake?
Bayes theorem: $P(A|B) = \frac{P(B|A) P(A)}{P(B)}$

In our case: $P(disease|test_+) = \frac{P(test_+|disease) P(disease)}{P(test_+)}$

Given:

$P(test_+|disease) = 0.85 \\
P(test_-|healthy) = 0.9 \\
P(disease) = 0.02$

Since a test can be positive while the patient has a disease and it also can be positive while the patient is healthy, the overall probability for a positive test is calculated as follows:

$P(test_+) = P(test_+|disease) P(disease) + P(test_+|healthy) P(healthy) \\
P(test_+|healthy) = 1 - P(test_-|healthy) \\
P(healthy) = 1 - P(disease)$

So:

$
\begin{align}
P(disease|test_+)
&amp;= \frac{P(test_+|disease) P(disease)}{P(test_+|disease) P(disease) + P(test_+|healthy) P(healthy)} \\
&amp;= \frac{P(test_+|disease) P(disease)}{P(test_+|disease) P(disease) + (1 - P(test_-|healthy)) (1 - P(disease))} \\
&amp;= \frac{0.85 \times 0.02}{0.85 \times 0.02 + (1 - 0.9) (1 - 0.02)} \\
&amp;= \frac{0.017}{0.017 + 0.1 \times 0.98} = \frac{0.017}{0.115} \approx 0.148
\end{align}
$

So, the probability that you have the disease given that you were tested positively is around 14,8% in this case.