Abstract: A diagnostic assay for determining presence of lung cancer in a patient depends, in part, on ascertaining the presence of an antibody associated with lung cancer using random polypeptides. The assay predicated lung cancer prior to evidence of radiographically detectable cancer tissue.

Abstract: A method for selecting a person at risk for lung cancer to undergo radiographic testing is provided. The method provides for the identification of markers for lung cancer in a population of patients that have not previously diagnosed with the disease. The markers identify autoantibodies present in a fluid sample of a patient who may not show other symptoms of lung cancer.

Abstract: A method for selecting a person at risk for lung cancer to undergo radiographic testing is provided. The method provides for the identification of markers for lung cancer in a population of patients that have not previously diagnosed with the disease. The markers identify autoantibodies present in a fluid sample of a patient who may not show other symptoms of lung cancer.

Abstract: A diagnostic assay for determining presence of lung cancer in a patient depends, in part, on ascertaining the presence of an antibody associated with lung cancer using random polypeptides. The assay predicted lung cancer prior to evidence of radiographically detectable cancer tissue.

Abstract: A diagnostic assay for determining presence of lung cancer in a patient depends, in part, on ascertaining the presence of an antibody associated with lung cancer. The assay predicted lung cancer prior to evidence of radiographically detectable cancer tissue.

Abstract: A method is provided for detecting or predicting an undesired deviation in variability of at least one parameter being monitored, wherein the variation in the parameter is incrementally recorded. The method comprises establishing the number of subsets of a dataset that have a range of the difference between any two datapoints within the dataset, and computing a control chart for the range based thereon. The method accurately detects changes in variability in real time. The true distribution of the data is reflected, and the desired result is achieved without requiring an inordinate number of computations.

Abstract: The method comprises establishing the number of subsets of a dataset that have a range of the difference between any two datapoints within the dataset, and computing a control chart for the range based thereon. In another aspect, a software program for accomplishing the method of the present invention is provided. The method of the invention allows monitoring variability of a product being produced by a particular piece of machinery, of a process conducted by the machinery, or of a product stream generated thereby, accurately detecting changes in variability in real time. The true distribution of the data is reflected, and the desired result is achieved without requiring an inordinate number of computations.