True positive/negative rates

In general the rate of false negatives are by definition difficult to ascertain. There are two general approaches to get a handle on false negatives. The first approach is based on what is known about the aqueous solubility of screening compounds since truly active compounds out of solution are the most common cause of false negatives. One can infer that perhaps 15% of true positives will be missed in an HTS. This inference comes from an analysis of the concordance or lack of concordance between nominal concentrations in DMSO stocks and nominal... 

In clinical chemistry and medical diagnostics the true positive rate is called sensitivity rate and the true negative rate specificity rate (O Rangers and Condon [2000]) without any relation to the general definition of the terms sensitivity and specificity and their use in analytical chemistry (see Sects. 7.2 and 7.3). 

PPR is the probability of obtaining positive responses, TPR true positive rate (Eq. 4.48), TNR true negative rate (Eq. 4.49), FPR false positive rate (Eq. 4.50), FNR false negative rate (Eq. 4.51), X/ and xu are the lower and upper limits of the unreliability region... 

These are well-known classification parameters true positive rate (p ), false positive rate (pnx), true negative rate (qnx), and false negative rate (qK). They can be easily obtained from the previous computations where we calculated the number of taxon and nontaxon members in each interval. For example, to calculate the true positive rate, we sum the number of taxon members in intervals above the hitmax, plus half of taxon members in the hitmax interval and divide this by the total number of taxon members in the sample. To calculate the false negative rate, we sum number of taxon members in intervals below the hitmax, plus half of the taxon members in the hitmax interval and divide this by the total number of taxon members in the sample. 

Such considerations have led to development of the concept of predictive power, which is more directly useful in evaluating the results from a screening instrument. Positive predictive power is the probability that a child identified by the instrument as having the disorder or symptom actually does have it, and negative predictive power is the probability that a child identified as not having the disorder or symptom actually does not have it. In some ways, predictive power is the converse of specificity and sensitivity, but it usually also depends on the base rate. If sensitivity is 100% then the negative predictive power would be 100%. If specificity is 100%, then positive predictive power is 100%. But when sensitivity and specificity are less than 100% (the usual situation), the base rate enters into the calculation. With 90% sensitivity, 90% specificity, and a 5% base rate, there are 4.5% true positives, 85.5%... 

True-positive and false-negative rates of the LEAP1 method as a function of search threshold for molecular similarity... 

The data on the true positive and true negative rates in conjunction with the drug use in the target population can be used to calculate the predictive value of the test. The predictive value is the percentage of true positives in a positive test population. 

Sn being the sensitivity (or the true positive rate, TPR or recall), Sp the specificity (or the true negative rate, TNR), FNR the false negative rate, FPR the false positive rate, PPV the positive predictive value (or precision), and NPV the negative predictive value. 

We have learned that it is possible to predict with about 80% accuracy (i.e., true positive and true negative predictions) clinically significant inhibitory metabolic DDIs arising from in vitro determination of the perpetrator s Kifor a specific GYP and a reasonable estimate of the perpetrator s in vivo concentration, [7]. Furthermore, it is likely that the accuracy rate can be increased by refining... 

Specificity is the measure of the true negative rate, which represents the ratio of true negatives (TN) to the total number of inactive compounds. The number of inactive compounds corresponds to both true negatives (TN) and false positives (FP) ... 

Most diagnostic tests are imperfect and, particularly when we use a binary approach - results are either "positive" or "negative" - there are some misclassification errors, inaccuracies. Some subjects with the condition of interest will be missed or some without the condition will be mistakenly considered affected, or both will happen. The ability of a test to properly identify or classify subjects or conditions of interest can be expressed as the sensitivity and specificity of the test. For clinical purposes these are defined as follows SENSITIVITY (TRUE POSITIVE RATE) Fraction of all affected... 

The ROC curve can also be constructed as a plot of true positive rate (sensitivity) versus true negative rate (specificity) instead of versus false positive rate... 

In addition, the Area Under the Curves (AUC) of the Receiver Operating Characteristic (ROC) curves were calculated as a quantitative measure for sensitivity and specificity of BIS to estimate the BAC. In a ROC curve, the True Positive Rate (TPR, sensitivity) is plotted against the False Positive Rate (FPR, 1-specificity). The TPR defines how many correct positive results occur among all positive samples and the FPR defines how many incorrect positive results occur among all negative samples. The AUC is then calculated as follows ... 

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