Robert C Soltysik
Datos Biográficos
| ID | 5544015 |
|---|---|
| NOMBRE | Robert C Soltysik |
| NOMBRES | Robert C |
| APELLIDO | Soltysik |
| FIRMA | SOLTYSIK R C |
| AFILIACIONES | Northwestern University Medical School |
| ORCID | 0000-0002-1342-502X |
| VERIFICADO | No |
| TOTAL DE OBRAS | 4 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 4 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 1994 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2007 |
| ÍNDICE H | 0 |
Development and Validation of a Short-Form, Rapid Estimate of Adult Literacy in Medicine
BACKGROUND: Although prior studies used the 66-item Rapid Estimate of Adult Literacy in Medicine (REALM instrument) for literacy assessment, researchers may require a shorter, validated instrument when designing interventions for clinical contexts. OBJECTIVE: To develop and validate a very brief literacy assessment tool, the REALM-Short Form (REALM-SF). PATIENTS: The model development, validation, and field testing validation samples included 133…
Developing Indicators of Inpatient Adverse Drug Events Through Nonlinear Analysis Using Administrative Data
BACKGROUND: Because of uniform availability, hospital administrative data are appealing for surveillance of adverse drug events (ADEs). Expert-generated surveillance rules that rely on the presence of International Classification of Diseases, 9th Revision Clinical Modification (ICD-9-CM) codes have limited accuracy. Rules based on nonlinear associations among all types of available administrative data may be more accurate. OBJECTIVES: By applying…
Univariable Optimal Discriminant Analysis
For applications involving a single attribute, univariable optimal discriminant analysis (UniODA) is appropriate when one desires to identify a discriminant classifier that explicitly maximizes classification accuracy for a given sample of data. An open-form enumerable solution for the theoretical distribution of optimal values (number of misclassifications) arising from two-category UniODA of continuous random data has recently been discovered, …
Optimizing the Classification Performance of Logistic Regression and Fisher'S Discriminant Analyses
Logistic regression analysis (LRA) and Fisher's discriminant analysis (FDA) are two of the most popular methodologies for solving classification problems involving a dichotomous class variable and two or more attributes. Like other suboptimal classification methodologies, neither LRA nor FDA explicitly maximizes percentage accuracy in classification (PAC) for the training sample (the sample on which the model is based). A heuristic is described t…
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Univariable Optimal Discriminant Analysis
For applications involving a single attribute, univariable optimal discriminant analysis (UniODA) is appropriate when one desires to identify a discriminant classifier that explicitly maximizes classification accuracy for a given sample of data. An open-form enumerable solution for the theoretical distribution of optimal values (number of misclassifications) arising from two-category UniODA of continuous random data has recently been discovered, …
Optimizing the Classification Performance of Logistic Regression and Fisher'S Discriminant Analyses
Logistic regression analysis (LRA) and Fisher's discriminant analysis (FDA) are two of the most popular methodologies for solving classification problems involving a dichotomous class variable and two or more attributes. Like other suboptimal classification methodologies, neither LRA nor FDA explicitly maximizes percentage accuracy in classification (PAC) for the training sample (the sample on which the model is based). A heuristic is described t…
Development and Validation of a Short-Form, Rapid Estimate of Adult Literacy in Medicine
BACKGROUND: Although prior studies used the 66-item Rapid Estimate of Adult Literacy in Medicine (REALM instrument) for literacy assessment, researchers may require a shorter, validated instrument when designing interventions for clinical contexts. OBJECTIVE: To develop and validate a very brief literacy assessment tool, the REALM-Short Form (REALM-SF). PATIENTS: The model development, validation, and field testing validation samples included 133…
Developing Indicators of Inpatient Adverse Drug Events Through Nonlinear Analysis Using Administrative Data
BACKGROUND: Because of uniform availability, hospital administrative data are appealing for surveillance of adverse drug events (ADEs). Expert-generated surveillance rules that rely on the presence of International Classification of Diseases, 9th Revision Clinical Modification (ICD-9-CM) codes have limited accuracy. Rules based on nonlinear associations among all types of available administrative data may be more accurate. OBJECTIVES: By applying…
Mathematics (3 obras) · Statistics (3 obras) · Artificial Intelligence (2 obras) · Artificial Intelligence (2 obras) · Computer Science (2 obras) · Face and Expression Recognition (2 obras) · Linear discriminant analysis (2 obras) · Medicine (2 obras) · Advanced Chemical Sensor Technologies (1 obras) · Advanced Statistical Methods and Models (1 obras)