Abstract: In one embodiment, a method includes, for each of a set of samples, receiving data input that includes dimensions of a sample area, a percentage of the sample area being viable cells, and a percentage of the sample area exhibiting necrosis. The method includes, for each of the set of samples, computing a percentage of the sample area being stroma. The method includes, for each of the set of samples, computing weighting factors. The method includes computing a weighted percentage of the set of samples being viable cells based on the computed weighting factor and percentage of the sample area being viable cells for each of the set of samples. The method includes determining that a specified condition is detected in the set of samples based on the computed weighted percentage of the set of samples being viable cells satisfying a threshold correlating with an indication of the specified condition.

Abstract: In one embodiment, a method includes, for each of a set of samples, receiving data input that includes dimensions of a sample area, a percentage of the sample area being viable cells, and a percentage of the sample area exhibiting necrosis. The method includes, for each of the set of samples, computing a percentage of the sample area being stroma. The method includes, for each of the set of samples, computing weighting factors. The method includes computing a weighted percentage of the set of samples being viable cells based on the computed weighting factor and percentage of the sample area being viable cells for each of the set of samples. The method includes determining that a specified condition is detected in the set of samples based on the computed weighted percentage of the set of samples being viable cells satisfying a threshold correlating with an indication of the specified condition.

Abstract: In one embodiment, a method includes, for each of a set of samples, receiving data input that includes dimensions of a sample area, a percentage of the sample area being viable cells, and a percentage of the sample area exhibiting necrosis. The method includes, for each of the set of samples, computing a percentage of the sample area being stroma. The method includes, for each of the set of samples, computing weighting factors. The method includes computing a weighted percentage of the set of samples being viable cells based on the computed weighting factor and percentage of the sample area being viable cells for each of the set of samples. The method includes determining that a specified condition is detected in the set of samples based on the computed weighted percentage of the set of samples being viable cells satisfying a threshold correlating with an indication of the specified condition.

Abstract: In one embodiment, a method includes, for each of a set of samples, receiving data input that includes dimensions of a sample area, a percentage of the sample area being viable cells, and a percentage of the sample area exhibiting necrosis. The method includes, for each of the set of samples, computing a percentage of the sample area being stroma. The method includes, for each of the set of samples, computing weighting factors. The method includes computing a weighted percentage of the set of samples being viable cells based on the computed weighting factor and percentage of the sample area being viable cells for each of the set of samples. The method includes determining that a specified condition is detected in the set of samples based on the computed weighted percentage of the set of samples being viable cells satisfying a threshold correlating with an indication of the specified condition.