A computer-implemented method involving a cancer scoring tool, the method comprising: (a) storing a false negative rate value and a false positive rate value for cell objects in the tool, wherein the false positive rate value is a number of cell objects that the tool identified in a training image as cells that an expert did not identify as cells per hundred and the false negative rate value is a number of cells that the expert did identify but that the tool improperly failed to identify as cell objects per hundred, wherein the false negative rate value and the false positive rate value are determined for a large number of training images and an overall false positive rate value and an overall false negative rate value are stored as the false negative rate value and the false positive rate value in the tool; (b) receiving a digital image into the tool, wherein the digital image is an image of a tissue sample of a cancer patient; (c) analyzing the digital image using a computerized cell identification procedure and thereby identifying a plurality of cell objects; (d) storing first information, wherein the first information stored in (d) is indicative of the plurality of cell objects identified in (c); (e) applying a scoring procedure on the first information thereby determining a first score; (f) adding a first number of cell objects to the plurality of cell objects identified in (c), wherein the first number is determined based on the false negative rate value; (g) subtracting a second number of the cell objects identified in (c), wherein the second number is determined based on the false positive rate value; (h) storing second information, wherein the second information stored in (h) is indicative of the plurality of cell objects identified in (c) as added to in (f) and as subtracted from in (g); (i) applying the scoring procedure on the second information thereby generating a second score; (j) repeating (f), (g), (h) and (i) a plurality of times, wherein at least some of the particular cell objects that are added in (f) and the particular cell objects that are subtracted in (g) are different each time, and wherein each time another second score is generated in (i) such that a plurality of second scores is determined; (k) determining a confidence number based on the plurality of second scores determined in (j); and (l) storing the confidence number in association with the first score on the tool, wherein (a) through are performed by the tool; wherein the first score is a number the magnitude of which is indicative of the severity of cancer in the tissue sample and/or is indicative of the probability of success of a particular treatment and/or is indicative of a cancer sub-type. (a) storing a false negative rate value and a false positive rate value for cell objects in the tool, wherein the false positive rate value is a number of cell objects that the tool identified in a training image as cells that an expert did not identify as cells per hundred and the false negative rate value is a number of cells that the expert did identify but that the tool improperly failed to identify as cell objects per hundred, wherein the false negative rate value and the false positive rate value are determined for a large number of training images and an overall false positive rate value and an overall false negative rate value are stored as the false negative rate value and the false positive rate value in the tool; (b) receiving a digital image into the tool, wherein the digital image is an image of a tissue sample of a cancer patient; (c) analyzing the digital image using a computerized cell identification procedure and thereby identifying a plurality of cell objects; (d) storing first information, wherein the first information stored in (d) is indicative of the plurality of cell objects identified in (c); (e) applying a scoring procedure on the first information thereby determining a first score; (f) adding a first number of cell objects to the plurality of cell objects identified in (c), wherein the first number is determined based on the false negative rate value; (g) subtracting a second number of the cell objects identified in (c), wherein the second number is determined based on the false positive rate value; (h) storing second information, wherein the second information stored in (h) is indicative of the plurality of cell objects identified in (c) as added to in (f) and as subtracted from in (g); (i) applying the scoring procedure on the second information thereby generating a second score; (j) repeating (f), (g), (h) and (i) a plurality of times, wherein at least some of the particular cell objects that are added in (f) and the particular cell objects that are subtracted in (g) are different each time, and wherein each time another second score is generated in (i) such that a plurality of second scores is determined; (k) determining a confidence number based on the plurality of second scores determined in (j); and (l) storing the confidence number in association with the first score on the tool, wherein (a) through are performed by the tool;