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Now showing items 85-104 of 310

Does family pressure for non-disclosure of a cancer diagnosis interfere with patients’ ability to cope?

Althoff, Christine (George Mason University, 2013-02-22)

Withholding prognosis information was associated with anxiety and difficulty with patient and family communication. Singapore, Chinese and Japanese patients prefer to be informed of cancer diagnosis and disease progression. ...
Does guideline adherence improve patient outcome in outpatient settings?

Ghimire, Prithvi (George Mason University, 2013-05-07)

Purpose: Heart Failure (HF) is a chronic disease associated with substantial morbidity, mortality and healthcare expenditure. According to a study done by Their et al. (2008), the two main reasons that lead to less than ...
Dynamic Recognition: An Outline of Theory of How to Recognize Concepts without Matching Rules

Michalski, Ryszard S. (1986)
El Nino Teleconnections Research: Initial Results Using a Machine Learning and Discovery Approach

Li, Zuotao; Kafatos, Menas; Michalski, Ryszard S. (1997)
EMERALD 1: An Integrated System of Machine Learning and Discovery Programs for Education and Research, User's Guide

Kaufman, Kenneth A.; Michalski, Ryszard S.; Schultz, Alan C. (1989)
EMERALD 1: An Integrated System of Machine Learning and Discovery Programs for Education and Research: Programmer's Guide for the Sun Workstation

Kaufman, Kenneth A.; Schultz, Alan C.; Michalski, Ryszard S. (1990-12)
EMERALD 1: An Integrated System of Machine Learning and Discovery Programs for Education and Research: Programmer's Guide for the VaxStation

Kaufman, Kenneth A.; Michalski, Ryszard S. (1990-12)
EMERALD 2: An Integrated System of Machine Learning and Discovery Programs for Education and Research Programmers Guide for the SUN Workstation

Kaufman, Kenneth A.; Schultz, Alan C.; Michalski, Ryszard S. (1993-09)
EMERALD 2: An Integrated System of Machine Learning and Discovery Programs for Education and Research User's Guide

Kaufman, Kenneth A.; Michalski, Ryszard S.; Schultz, Alan C. (1993-09)
EMERALD 2: An Integrated System of Machine Learning and Discovery Programs for Education and Research, Programmer's Guide for the Sun Workstation (Updated Edition)

Kaufman, Kenneth A.; Michalski, Ryszard S. (1997)
EMERALD 2: An Integrated System of Machine Learning and Discovery Programs for Education and Research, User's Guide (Updated Edition)

Kaufman, Kenneth A.; Michalski, Ryszard S. (1997)
EMERALD 2: An Integrated System of Machine Learning and Discovery Programs to Support Education and Experimental Research

Kaufman, Kenneth A.; Michalski, Ryszard S. (1993-09)
The Emerging Field of Travel Training Services: A Systems Perspective

Wolf-Branigin, Michael; Wolf-Branigin, Karen (2008)

Travel training provides a promising approach for moving persons from paratransit to fixed-route transportation services. This study identifies current funding trends and discusses the volume and diversity of services ...
An Empirical Comparison Between Learning Decision Trees from Examples and from Decision Rules

Imam, Ibrahim F.; Michalski, Ryszard S. (1996-10)
An Evaluation Synthesis of US AIDS Drug Assistance Program Policy

Horneffer, Michael A.; Yang, Y. Tony (Scientific Research, 2013-06)

US Congress passed the CARE Act in 1990 in response to a dramatically growing need for resources to combat the AIDS epidemic. One of the programs contained in the Act was the AIDS Drug Assistance Program (ADAP), a ...
An Experiment on Inductive Learning in Chess End Games

Michalski, Ryszard S.; Negri, Pericles (1977)
An Experimental Application of the Learnable Evolution Model and Genetic Algorithms to Parameter Estimation in Digital Signal Filters Design

Coletti, Mark; Lash, Thomas D.; Mandsager, Craig; Moustafa, Rida E.; Michalski, Ryszard S. (1999-05)
An Experimental Comparison of Symbolic and Subsymbolic Learning Paradigms: Phase I -- Learning Logic-Style Concepts

Wnek, Janusz; Michalski, Ryszard S. (1991-11)
Experimental Validations of the Learnable Evolution Model

Cervone, Guido; Kaufman, Kenneth A.; Michalski, Ryszard S. (2000-07)

A recently developed approach to evolutionary computation, called Learnable Evolution Model or LEM, employs machine learning to guide processes of generating new populations. The central new idea of LEM is that it generates ...
An Expert System to Assist Turfgrass Managers in Weed Identification

Fermanian, Thomas W.; Michalski, Ryszard S.; Katz, Bruce (1985-07)

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