| D008390 |
Markov Chains |
A stochastic process such that the conditional probability distribution for a state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system. |
Markov Process,Markov Chain,Chain, Markov,Chains, Markov,Markov Processes,Process, Markov,Processes, Markov |
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| D008958 |
Models, Molecular |
Models used experimentally or theoretically to study molecular shape, electronic properties, or interactions; includes analogous molecules, computer-generated graphics, and mechanical structures. |
Molecular Models,Model, Molecular,Molecular Model |
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| D009419 |
Nerve Tissue Proteins |
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Proteins, Nerve Tissue,Tissue Proteins, Nerve |
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| D004546 |
Elapid Venoms |
Venoms from snakes of the family Elapidae, including cobras, kraits, mambas, coral, tiger, and Australian snakes. The venoms contain polypeptide toxins of various kinds, cytolytic, hemolytic, and neurotoxic factors, but fewer enzymes than viper or crotalid venoms. Many of the toxins have been characterized. |
Cobra Venoms,Elapidae Venom,Elapidae Venoms,Naja Venoms,Cobra Venom,Elapid Venom,Hydrophid Venom,Hydrophid Venoms,King Cobra Venom,Naja Venom,Ophiophagus hannah Venom,Sea Snake Venom,Sea Snake Venoms,Venom, Cobra,Venom, Elapid,Venom, Elapidae,Venom, Hydrophid,Venom, King Cobra,Venom, Naja,Venom, Ophiophagus hannah,Venom, Sea Snake,Venoms, Cobra,Venoms, Elapid,Venoms, Elapidae,Venoms, Hydrophid,Venoms, Naja,Venoms, Sea Snake |
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| D000465 |
Algorithms |
A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. |
Algorithm |
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| D001499 |
Bayes Theorem |
A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. |
Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes |
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| D012372 |
ROC Curve |
A graphic means for assessing the ability of a screening test to discriminate between healthy and diseased persons; may also be used in other studies, e.g., distinguishing stimuli responses as to a faint stimuli or nonstimuli. |
ROC Analysis,Receiver Operating Characteristic,Analysis, ROC,Analyses, ROC,Characteristic, Receiver Operating,Characteristics, Receiver Operating,Curve, ROC,Curves, ROC,ROC Analyses,ROC Curves,Receiver Operating Characteristics |
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| D015203 |
Reproducibility of Results |
The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results. |
Reliability and Validity,Reliability of Result,Reproducibility Of Result,Reproducibility of Finding,Validity of Result,Validity of Results,Face Validity,Reliability (Epidemiology),Reliability of Results,Reproducibility of Findings,Test-Retest Reliability,Validity (Epidemiology),Finding Reproducibilities,Finding Reproducibility,Of Result, Reproducibility,Of Results, Reproducibility,Reliabilities, Test-Retest,Reliability, Test-Retest,Result Reliabilities,Result Reliability,Result Validities,Result Validity,Result, Reproducibility Of,Results, Reproducibility Of,Test Retest Reliability,Validity and Reliability,Validity, Face |
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| D015233 |
Models, Statistical |
Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. |
Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model |
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| D016013 |
Likelihood Functions |
Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters. |
Likelihood Ratio Test,Maximum Likelihood Estimates,Estimate, Maximum Likelihood,Estimates, Maximum Likelihood,Function, Likelihood,Functions, Likelihood,Likelihood Function,Maximum Likelihood Estimate,Test, Likelihood Ratio |
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