Skychain March 2021 project development update

Preparation

Results

This is the example of doctor’s opinion on one of the patients:
Slide 1: O, PIN, Gleason Score 3 + 4 = 7, occupies 30% of the punctate length.
Slide 2: O, PIN, Gleason Score 4 + 3 = 7, occupies 100% of the punctate length.
Slide 3: O, Gleason Score 3 + 4 = 7 points, occupies 90% of the punctate length.
Slide4: O, PIN, Gleason Score 3 + 3 = 6 points, occupies 90% of the punctate length.
Slide 5: O, PIN, Gleason Score 3 + 3 = 6 points, occupies 90% of the punctate length.
Slide 6: O, PIN, Gleason Score 3 + 3 = 6 points, occupies 80% of the punctate length.
Slide 7: O, Gleason Score 4 + 4 = 8 points, occupies 50% of the punctate length.
Slide 8: O, Gleason Score 4 + 3 = 7 points, occupies 40% of the punctate length.
Slide 9: O, PIN, Gleason Score 4 + 4 = 8 points, takes 50% of the punctate length.
Slide 10: O, Gleason Score 5 + 5 = 10 points, occupies 40% of the punctate length.
Slide 11: O, Gleason Score 5 + 5 = 10 points, occupies 90% of the punctate length.
Slide 12: N, small columns of prostate tissue without tumor growth.

Explanation: Cohen’s kappa measures agreement between two evaluators, each classifying N elements in C mutually exclusive categories. In our case, the Cohen’s kappa will be calculated on 108 test slides for N experts + the prediction of our neural network, that is, we will get N + 1 values.

Cohen’s Kappa Formula:

where pо is the relative observable agreement between the evaluators (identical in accuracy), and pе is the hypothetical probability of a random agreement, using the observed data to calculate the likelihood of each observer randomly seeing each category.

X-axis — doctors making a diagnosis + neural network, Y-axis — Cohen’s kappa. This diagram shows the distribution of Cohen’s kappa for 2 doctors and the neural network. The legend on the bottom left in color indicates the belonging to each of the classes. The graph displays the minimum / maximum value. The body of the candlestick is calculated as the median value + — the standard deviation.
X-axis — doctors making a diagnosis + neural network, Y-axis — Cohen’s kappa. The different colors correspond to different doctors for clarity.

In general, we can conclude that Skychain has outperformed both experts in several classes and showed quite comparable results in others.

But what about the time?

Curious case

Tissue sample. As you can see, it has some few blue areas, which mean that Skychain neural network sees it as cancer.

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