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PubMed1995

Dependent masking and system life data analysis: Bayesian inference for two-component systems.

Data from field operations of a system is often used to estimate the reliability of components. Under ideal circumstances, this system field data contains the time to failure along with information on the exact component responsible for the system failure. However, in many cases, the exact component causing the failure of the system cannot be identified, and is considered to be masked. Previously developed models for estimation of component reliability from masked system life data have been based upon the assumption that masking occurs independently of the true cause of system failure. In this paper we develop a Bayesian methodology for estimating component reliabilities from masked system life data when the probability of masking is dependent upon the true cause of system failure. The Bayesian approach is illustrated for the case of a two-component system of exponentially distributed components.

Bayes Theorem↗
PubMed1987

Prediction of 1-year outcome after complicated and uncomplicated myocardial infarction: Bayesian analysis of predischarge exercise test results in 300 patients.

After myocardial infarction (MI), the additive prognostic value of exercise variables to clinical variables has been questioned. The merits of a symptom-limited predischarge exercise test were therefore evaluated in clinically defined subgroups of patients. Exercise tests were consecutively performed by 208 survivors of uncomplicated MI (no heart failure, postinfarction angina, recurrent infarction, or late arrhythmias) and by 92 survivors of complicated MI. After uncomplicated MI (1-year mortality rate 4%), an achieved workload greater than 70% of age-predicted maximum identified 145 patients at very low risk (predictive value for survival 98%). After complicated MI (1-year mortality rate 13%), an exaggerated heart rate response was the best predictor of outcome, but had low (92%) predictive value of survival at 155 bpm. It is concluded that stress testing has only limited value after complicated MI. After uncomplicated MI, exercise variables are extremely helpful in identifying patients at very low risk in whom further investigations are not warranted.

Adult↗
PubMed1984

Bayesian analysis using Fourier transforms of thallium-201 scintiscans to predict the presence of coronary artery disease.

Bayes' theorem of conditional probability was applied to the diagnosis of coronary artery disease (CAD) using thallium-201 scintigraphy as the testing procedure. Thallium-201 scintiscans were evaluated with a discriminant function previously developed using the amplitude coefficients of the Fourier transforms of the scans. The technique was applied prospectively to a population of 100 patients undergoing diagnostic coronary arteriography and thallium-201 scintigraphy, including 83 patients with CAD (70% or greater stenosis of luminal diameter) and 17 control subjects. A pretest probability of CAD was determined for each patient from the patient's age, sex and anginal symptoms. The pretest probability was combined with the patient's discriminant score to determine a posttest probability for CAD. For patients with CAD, the mean posttest probability was 0.85. Moreover, 57 of 83 patients (69%) had posttest probabilities exceeding 90%, including 40 patients (48%) with posttest probabilities exceeding 99%. For control subjects, the mean posttest probability was 0.19, with 11 of 17 (65%) having a posttest probability of less than 10%. Overall, 68 subjects had a posttest probability either less than 10% or more than 90% of which 63 were correctly classified (93%). Using a 50% posttest probability as a cutoff for classification, the technique has an 89% sensitivity, an 82% specificity and an overall accuracy of 88%. Therefore, this method objectively distinguishes patients with CAD from control subjects and provides a measure of the certainty of diagnosis. In addition, the discriminant function avoids the problem of inter- and intraobserver variability in visually interpreting thallium-201 scans.

Adult↗
PubMed1995

The utility of three predictors of childhood myopia: a Bayesian analysis.

Any treatment to prevent the onset of juvenile myopia will require predictive tests in order to determine which children should receive treatment. Three risk factors for myopia were evaluated for their ability to predict myopia: (a) refraction at school entry; (b) refraction in infancy; and (c) parental history of myopia. Bayes' theorem was used to estimate these conditional probabilities. Refraction at school entry had twice the power to predict myopia (probability of juvenile myopia given the child is near emmetropia at school entry = 0.53) compared to either infant refraction (0.21-0.28) or parental myopia (0.20-0.25). While a history of any parent having myopia had the highest test sensitivity (probability of a positive family history of myopia given juvenile myopia in the child = 0.90) and refraction at school entry the highest test specificity (probability of more hyperopia than +0.50 D at school entry given no juvenile myopia = 0.91), none of these three factors had high values for both sensitivity and specificity. Further work is required to develop a battery of tests which could predict the onset of juvenile myopia with both adequate sensitivity and specificity.

Age Factors↗
PubMed1995

Bayesian analysis of identification performance in monkey visual cortex: nonlinear mechanisms and stimulus certainty.

The identification performance of single neurons in the primary visual cortex was quantified by measuring how accurately one could know the stimulus based upon the neuron's response. We found that for a typical neuron a response of 10 action potentials, following one brief stimulus presentation, was sufficient to classify the stimulus as belonging to a relatively small region in stimulus space, with a high degree of confidence. The performance was better than that which could be attained through linear summation of excitation and inhibition alone. The results suggest that the enhanced performance is a consequence of two nonlinear mechanisms: contrast gain control and expansive response exponent.

Action Potentials↗
PubMed1977

Bayesian analysis of electrocardiographic exercise stress testing.

We evaluated the diagnostic accuracy of exercise-induced ST-segment depression in detecting coronary-artery disease by applying the likelihood-ratio formulation of Bayes's theorem to stress-test data, which were partitioned into half-millimeter ranges of depression. The graphic relation between the predictive value of a given test result and the pretest risk of disease in the test subjects was obtained for each of these half-millimeter intervals. This method reveals that the predictive value of testing depends on the degree of ST-segment depression, and that the pretest risk of coronary-artery disease is an important determinant of the predictive value of any test result in the individual patient. These findings suggest that the use of the terms "positive" and "negative" are inappropriate to describe most stress-test results. Instead, the results should be interpreted in terms of a continuum of risk based on the extent of ST-segment depression.

Adult↗
PubMedDate not supplied

Recall and recognition as diagnostic indices of Malignant Memory Loss in Senile Dementia: a Bayesian analysis.

The Benign Senescent Forgetfulness of normal aging and the Malignant Memory Loss of Senile Dementia of the Alzheimer Type (SDAT) each have a distinct symptomatology, course, and prognosis. The purpose of this study was to evaluate the discriminative validity and relative predictive values of recall and recognition as diagnostic screening tests for the Malignant Memory Loss of SDAT. Thirty-six patients with mild to moderate SDAT and 40 normal aged controls were studied. Both recall and recognition showed good discriminative validity. However, analysis of recall and recognition by Bayes's Theorem revealed the relative predictive values as diagnostic screening instruments were 11% and 100% respectively. Thus, it was concluded that while both recall and recognition have discriminative validity under experimental conditions, a test of recognition is the preferred diagnostic instrument when screening for the Malignant Memory Loss of SDAT.

Aged↗
PubMed2002

Bayesian analysis and inference from QSAR predictive model results.

QSAR models have been under development for decades but acceptance and utilization of model results have been slow, in part, because there is no widely accepted metric for assessing their reliability. We reapply a method commonly used in quantitative epidemiology and medical decision-making for evaluating the results of screening tests to assess reliability of a QSAR model. It quantifies the accuracy (expressed as sensitivity and specificity) of QSAR models as conditional probabilities of correct and incorrect classification of chemical characteristic, given a true characteristic. Using Bayes formula, these conditional probabilities are combined with prior information to generate a posterior distribution to determine the probability a specific chemical has a particular characteristic, given a model prediction. As an example, we apply this approach to evaluate the predictive reliability of a CATABOL model and base on it a "ready" and "not ready" biodegradability classification. Finally, we show how predictive capability of the model can be improved by sequential use of two models, the first one with high sensitivity and the second with high specificity.

Bayes Theorem↗
PubMed1983

Bayesian analysis of stress thallium scintigraphy for the detection of multivessel coronary disease.

This study was performed in 224 men to determine the respective contribution of history and thallium-201 stress myocardial scintigraphic imaging in the non-invasive prediction of the severity of coronary disease. Myocardial scintigraphic imaging had the better diagnostic accuracy (80%) for the detection of multivessel disease but the results emphasize the importance of the history in predicting the extent of coronary artery disease. In patients with myocardial infarction, the diagnostic accuracy of the history (80%) was similar to the diagnostic accuracy of myocardial scintigraphic imaging (79%); in the subgroup of patients with residual angina pectoris after infarction, the accuracy of the history was even greater (87%) than that of myocardial scintigraphic imaging (78%). Thus, after myocardial infarction, scintigraphy was useful only in the small subgroup of patients without residual angina pectoris when it had a diagnostic accuracy of 79%, slightly but insignificantly superior to that of the history (62%). In patients without previous myocardial infarction, but with typical angina, myocardial scintigraphy was clearly superior to the simple history (diagnostic accuracy of 78% versus 53%; P less than 0.001). In patients without myocardial infarction and with atypical angina the prevalence of multivessel disease was low (17%) and the diagnostic accuracy of history (83%) was barely different from the diagnostic accuracy of myocardial scintigraphic imaging (90%). Thus, when the likelihood of multivessel disease is very high (angina pectoris post myocardial infarction), or very low (atypical angina), the contribution of exercise testing is very limited. Important additional information is provided by maximal exercise testing and myocardial scintigraphic imaging only in the groups with an intermediate prevalence of multivessel disease, namely in the asymptomatic patients after myocardial infarction and in the patients with typical angina but no previous myocardial infarction.

Angiography↗
PubMed2003

Bayesian analysis of data: reconstruction of track structure at 100% detection efficiency for a track-nanodosimetric counter.

An algorithmic reconstruction of the probability distribution of ionisation cluster-size formation from measurements performed with detectors having a non-uniform sensitive volume is presented. From such a data analysis, ionisation spectra, which correspond to a detection efficiency of 100% are extracted for the track-nanodosimetric counter at L.N.L.-I.N.F.N.

Algorithms↗
PubMed2001

Estimating the posterior probability of LTP failure by sequential Bayesian analysis of an imperfect Bernoulli trial model.

A tetanically stimulated (TS) neuron is said to have failed to fire if its voltage-clamped excitatory postsynaptic current (EPSC) measurement is devoid of a long-term potentiation (LTP) response. This paper provides a method for evaluating the posterior probability of "failure" for TS neurons. A sequential Bayes algorithm is employed on an imperfect Bernoulli trial model to refine the posterior with each EPSC data record processed. The method is applied to both real and simulated LTP data and is shown to be consistent with the theoretical Beta-distributed posterior and the reported in vitro voltage-clamped EPSC failure rates.

Algorithms↗
PubMed1999

Bayesian analysis.

Explore the source record for details and available documents.

Bayes Theorem↗
PubMed1993

Determining the likelihood of malignancy in solitary pulmonary nodules with Bayesian analysis. Part I. Theory.

Only two radiographic findings allow reliable distinction of benign from malignant solitary pulmonary nodules. Intuitively, it is clear that other radiographic and clinical findings should also be important in making this distinction. Subjectively incorporating these other findings into the decision of whether a nodule is benign or malignant is difficult. Likelihood ratios, which indicate the degree of malignancy or benignity represented by a test result or clinical finding, can be combined by means of the Bayes theorem to quantitate the probability of malignancy of a given nodule. From a literature survey, likelihood ratios were derived for six radiographic and four clinical characteristics associated with solitary pulmonary nodules. There were a total of 15 malignant and 19 benign findings, the most important of which were radiographic characteristics. For malignant nodules, the most important radiographic characteristics were thickness of the cavity wall spicular edge, and diameter of over 3 cm. For benign nodules, the most important radiographic characteristics were benign growth rate and a benign pattern of calcification.

Adult↗
PubMedDate not supplied

Bayesian analysis of diastolic blood pressure measurement.

A mathematical model is presented for measurements that include substantial fluctuation and error. Under the assumptions that the fluctuation-error variance is the same for all subjects, and that the distributions of fluctuation-error variance within subjects and "true" values of the measurements in the population are normal, Bayes' theorem produces a simple estimate of the "true" value of a measurement, and a standard error, conditional on a single observation. The model is easily extended to several observations. Methods for estimating the parameters of the model from a data set are presented, and applied to diastolic blood pressures of patients in the authors' primary care clinic. The test-retest reliability of a single blood pressure measurement for this population is 0.41. Because continuous measurements are often dichotomized into "normal" and "abnormal" ranges by a threshold criterion, the authors present formulas for the positive predictive value when a decision rule based on a given number of observations is used in a population with respect to a threshold criterion for the "true" values. For example, classifying their patients as hypertensive on the basis of the average of two readings exceeding 90 mm Hg diastolic pressure would have a positive predictive value of 52% for the "gold standard" of average diastolic pressure exceeding 90 mm Hg. Formulas to calculate the frequency with which patients will be classified "abnormal" by one decision rule but will be classified "normal" by later application of another rule are provided and used to "predict" the frequency with which this crossover phenomenon should have occurred in the enrollment phase of the Hypertension Detection and Follow-up Programs.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗