We can change the requirements, but we cannot reduce the overlap between the two distributions, or the sensitivity of the test without a change in data collection. If the criteria are made stricter to avoid unnecessary biopsies, the probability of missing cancerous samples also decreases. This relationship between false and true positives hints at the fundamental problem seen in mammography. However, in doing this, the number of true-positives detected also decreases. There will be some overlap between the two groups, and it is where we place our 'critical' threshold that will determine how many times we get a correct 'hit' or an incorrect 'false alarm.' One way to decrease the probability of a false positive would be to move the criteria threshold further to the right. Signal detection theory allows for the evaluation of the probability of a false-positives vs. the probability of a true-positives or 'hit.' Imagine two distributions, one that gives the population of samples that are noise and a second that has the distribution of samples that contain the signal that we are looking for that is slightly to the right of the first distribution. Signal detection theory allows not only for a clear determination of when a screening technique is inaccurate, but can also be used in the comparison of different test to determine which methodology is best at detecting the signal from the noise. However, new data has emerged surrounding the negative psychological consequences of false-positives in mammography.Īs a result, we not only need new methodologies, but also a method to evaluate the effectiveness of new breast cancer screening techniques. The implications for a false positive in a mammogram seem low compared to sending an innocent person to prison. The difference in the false positive probability between latent fingerprint examination and breast cancer screening also demonstrates how consequences factor into decision making. While these two examples represent two opposite ends of the spectrum, one with a very low false positive rate, the other with a very high one, they belie vital elements behind decision making and allow us to quantify how often we come to the correct conclusion. However, unlike fingerprint examining, mammography has a very high false positive rate, with thousands of women being called back for unnecessary biopsies and surgeries every year (2). Hundreds of thousands of women received annual mammograms to identify abnormal tissue within the breast. Mammograms, widely used early detection screenings for breast cancer, were introduced in the early 1960s and was were widely hailed as a method of detecting early stage breast cancer (1). Research has demonstrated that, as a whole, latent fingerprint examining has a very low false positive rate (3). She was later exonerated in 2010 after a private fingerprint investigator found that the print recovered at the scene was not a match for Canen’s. This case represents one of the relatively few false positives that exist within the field of latent print examination. At 44 years of age, she received a sentence of 55 years in prison. In 2002, a jury convicted Lana Canen of the murder of Helen Sailor based primarily on a partial fingerprint found on a pill bottle in the victim’s house in Elkhart, IN.

Detection theory