| D008297 |
Male |
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Males |
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| D012044 |
Regression Analysis |
Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. |
Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions |
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| D001932 |
Brain Neoplasms |
Neoplasms of the intracranial components of the central nervous system, including the cerebral hemispheres, basal ganglia, hypothalamus, thalamus, brain stem, and cerebellum. Brain neoplasms are subdivided into primary (originating from brain tissue) and secondary (i.e., metastatic) forms. Primary neoplasms are subdivided into benign and malignant forms. In general, brain tumors may also be classified by age of onset, histologic type, or presenting location in the brain. |
Brain Cancer,Brain Metastases,Brain Tumors,Cancer of Brain,Malignant Primary Brain Tumors,Neoplasms, Intracranial,Benign Neoplasms, Brain,Brain Neoplasm, Primary,Brain Neoplasms, Benign,Brain Neoplasms, Malignant,Brain Neoplasms, Malignant, Primary,Brain Neoplasms, Primary Malignant,Brain Tumor, Primary,Brain Tumor, Recurrent,Cancer of the Brain,Intracranial Neoplasms,Malignant Neoplasms, Brain,Malignant Primary Brain Neoplasms,Neoplasms, Brain,Neoplasms, Brain, Benign,Neoplasms, Brain, Malignant,Neoplasms, Brain, Primary,Primary Brain Neoplasms,Primary Malignant Brain Neoplasms,Primary Malignant Brain Tumors,Benign Brain Neoplasm,Benign Brain Neoplasms,Benign Neoplasm, Brain,Brain Benign Neoplasm,Brain Benign Neoplasms,Brain Cancers,Brain Malignant Neoplasm,Brain Malignant Neoplasms,Brain Metastase,Brain Neoplasm,Brain Neoplasm, Benign,Brain Neoplasm, Malignant,Brain Neoplasms, Primary,Brain Tumor,Brain Tumors, Recurrent,Cancer, Brain,Intracranial Neoplasm,Malignant Brain Neoplasm,Malignant Brain Neoplasms,Malignant Neoplasm, Brain,Neoplasm, Brain,Neoplasm, Intracranial,Primary Brain Neoplasm,Primary Brain Tumor,Primary Brain Tumors,Recurrent Brain Tumor,Recurrent Brain Tumors,Tumor, Brain |
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| D005260 |
Female |
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Females |
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| D006801 |
Humans |
Members of the species Homo sapiens. |
Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man |
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| D001254 |
Astrocytoma |
Neoplasms of the brain and spinal cord derived from glial cells which vary from histologically benign forms to highly anaplastic and malignant tumors. Fibrillary astrocytomas are the most common type and may be classified in order of increasing malignancy (grades I through IV). In the first two decades of life, astrocytomas tend to originate in the cerebellar hemispheres; in adults, they most frequently arise in the cerebrum and frequently undergo malignant transformation. (From Devita et al., Cancer: Principles and Practice of Oncology, 5th ed, pp2013-7; Holland et al., Cancer Medicine, 3d ed, p1082) |
Astrocytoma, Subependymal Giant Cell,Glioma, Astrocytic,Oligoastrocytoma, Mixed,Pleomorphic Xanthoastrocytomas,Anaplastic Astrocytoma,Astrocytoma, Grade I,Astrocytoma, Grade II,Astrocytoma, Grade III,Astrocytoma, Protoplasmic,Astroglioma,Cerebral Astrocytoma,Childhood Cerebral Astrocytoma,Fibrillary Astrocytoma,Gemistocytic Astrocytoma,Intracranial Astrocytoma,Juvenile Pilocytic Astrocytoma,Pilocytic Astrocytoma,Subependymal Giant Cell Astrocytoma,Anaplastic Astrocytomas,Astrocytic Glioma,Astrocytic Gliomas,Astrocytoma, Anaplastic,Astrocytoma, Cerebral,Astrocytoma, Childhood Cerebral,Astrocytoma, Fibrillary,Astrocytoma, Gemistocytic,Astrocytoma, Intracranial,Astrocytoma, Juvenile Pilocytic,Astrocytoma, Pilocytic,Astrocytomas,Astrocytomas, Grade III,Astrogliomas,Cerebral Astrocytoma, Childhood,Cerebral Astrocytomas,Childhood Cerebral Astrocytomas,Fibrillary Astrocytomas,Gemistocytic Astrocytomas,Gliomas, Astrocytic,Grade I Astrocytoma,Grade I Astrocytomas,Grade II Astrocytoma,Grade II Astrocytomas,Grade III Astrocytoma,Grade III Astrocytomas,Intracranial Astrocytomas,Juvenile Pilocytic Astrocytomas,Mixed Oligoastrocytoma,Mixed Oligoastrocytomas,Pilocytic Astrocytoma, Juvenile,Pilocytic Astrocytomas,Pleomorphic Xanthoastrocytoma,Protoplasmic Astrocytoma,Protoplasmic Astrocytomas,Xanthoastrocytoma, Pleomorphic |
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| D012307 |
Risk Factors |
An aspect of personal behavior or lifestyle, environmental exposure, inborn or inherited characteristic, which, based on epidemiological evidence, is known to be associated with a health-related condition considered important to prevent. |
Health Correlates,Risk Factor Scores,Risk Scores,Social Risk Factors,Population at Risk,Populations at Risk,Correlates, Health,Factor, Risk,Factor, Social Risk,Factors, Social Risk,Risk Factor,Risk Factor Score,Risk Factor, Social,Risk Factors, Social,Risk Score,Score, Risk,Score, Risk Factor,Social Risk Factor |
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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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| D016015 |
Logistic Models |
Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor. |
Logistic Regression,Logit Models,Models, Logistic,Logistic Model,Logistic Regressions,Logit Model,Model, Logistic,Model, Logit,Models, Logit,Regression, Logistic,Regressions, Logistic |
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| D016022 |
Case-Control Studies |
Comparisons that start with the identification of persons with the disease or outcome of interest and a control (comparison, referent) group without the disease or outcome of interest. The relationship of an attribute is examined by comparing both groups with regard to the frequency or levels of outcome over time. |
Case-Base Studies,Case-Comparison Studies,Case-Referent Studies,Matched Case-Control Studies,Nested Case-Control Studies,Case Control Studies,Case-Compeer Studies,Case-Referrent Studies,Case Base Studies,Case Comparison Studies,Case Control Study,Case Referent Studies,Case Referrent Studies,Case-Comparison Study,Case-Control Studies, Matched,Case-Control Studies, Nested,Case-Control Study,Case-Control Study, Matched,Case-Control Study, Nested,Case-Referent Study,Case-Referrent Study,Matched Case Control Studies,Matched Case-Control Study,Nested Case Control Studies,Nested Case-Control Study,Studies, Case Control,Studies, Case-Base,Studies, Case-Comparison,Studies, Case-Compeer,Studies, Case-Control,Studies, Case-Referent,Studies, Case-Referrent,Studies, Matched Case-Control,Studies, Nested Case-Control,Study, Case Control,Study, Case-Comparison,Study, Case-Control,Study, Case-Referent,Study, Case-Referrent,Study, Matched Case-Control,Study, Nested Case-Control |
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