Selection of Clinical Trials: Knowledge Representation and Acquisition

When medical researchers test a new treatment procedure, they recruit patients with appropriate health problems and medical histories. An experiment with a new procedure is called a clinical trial. The selection of patients for clinical trials has traditionally been a labor-intensive task, which involves matching of medical records with a list of eligibility criteria. A recent project at the University of South Florida has been aimed at the automation of this task. The project has involved the development of an expert system that selects matching clinical trials for each patient. If a patient\u27s data are not sufficient for choosing a trial, the system suggests additional medical tests. We report the work on the representation and entry of the related selection criteria and medical tests. We first explain the structureof the system\u27s knowledge base, which describes clinical trials and criteria for selecting patients. We then present an interface that enables a clinician to add new trials and selection criteria without the help of a programmer. Experiments show that the addition of a new clinical trial takes ten to twenty minutes, and that novice users learn the full functionality of the interface in about an hour

Selection of Clinical Trials: Knowledge Representation and Acquisition

When medical researchers test a new treatment procedure, they recruit patients with appropriate health problems and medical histories. An experiment with a new procedure is called a clinical trial. The selection of patients for clinical trials has traditionally been a labor-intensive task, which involves matching of medical records with a list of eligibility criteria. A recent project at the University of South Florida has been aimed at the automation of this task. The project has involved the development of an expert system that selects matching clinical trials for each patient. If a patient\u27s data are not sufficient for choosing a trial, the system suggests additional medical tests. We report the work on the representation and entry of the related selection criteria and medical tests. We first explain the structureof the system\u27s knowledge base, which describes clinical trials and criteria for selecting patients. We then present an interface that enables a clinician to add new trials and selection criteria without the help of a programmer. Experiments show that the addition of a new clinical trial takes ten to twenty minutes, and that novice users learn the full functionality of the interface in about an hour

Knowledge Acquisition for Clinical-Trial Selection

When medical researchers test a new treatment procedure, they recruit patients with appropriate medical histories. An experiment with a new procedure is called a clinical trial. The selection of patients for clinical trials has traditionally been a labor-intensive task, which involves the matching of medical records with a list of eligibility criteria, and studies have shown that clinicians can miss up to 60% of the eligible patients. A recent project at the University of South Florida has been aimed at the automation of this task. We have developed an intelligent agent that selects trials for eligible patients. We report the work on the representation and entry of the related knowledge about clinical trials. We describe the structure of the agent's knowledge base and the interface for adding new trials

Selection of patients for clinical trials: An interactive web-based system

The purpose of a clinical trial is to evaluate a new treatment procedure. When medical researchers conduct a trial, they recruit participants with appropriate health problems and medical histories. To select participants, they analyze medical records of the available patients, which has traditionally been a manual procedure. We describe an expert system that helps to select patients for clinical trials. If the available data are insufficient for choosing patients, the system suggests additional medical tests and finds an ordering of the tests that reduces their total cost. Experiments show that the system can increase the number of selected patients. We also present an interface that enables a medical researcher to add clinical trials and selection criteria without the help of a programmer. The addition of a new trial takes 10–20 min, and novice users learn the functionality of the interface in about an hour

Selection of patients for clinical trials: An interactive web-based system

The purpose of a clinical trial is to evaluate a new treatment procedure. When medical researchers conduct a trial, they recruit participants with appropriate health problems and medical histories. To select participants, the researchers analyze medical records of the available patients, which has traditionally been a manual procedure. We describe an expert system that helps to select patients for clinical trials. If the available data are insufficient for choosing patients, the system suggests additional medical tests and finds an ordering of the tests that reduces their total cost. Experiments show that the system can increase the number of selected patients. We also present an interface that enables a medical researcher to add clinical trials and selection criteria without the help of a programmer. The addition of a new trial takes ten to twenty minutes, and novice users learn the functionality of the interface in about an hour

Knowledge Acquisition for Clinical-Trial Selection

When medical researchers test a new treatment procedure, they recruit patients with appropriate medical histories. An experiment with a new procedure is called a clinical trial. The selection of patients for clinical trials has traditionally been a labor-intensive task, which involves the matching of medical records with a list of eligibility criteria, and studies have shown that clinicians can miss up to 60% of the eligible patients. A recent project at the University of South Florida has been aimed at the automation of this task. We have developed an intelligent agent that selects trials for eligible patients. We report the work on the representation and entry of the related knowledge about clinical trials. We describe the structure of the agent's knowledge base and the interface for adding new trials