The application of the intelligent monitoring techniques of case-based reasoning and neural network analysis to physician decision making concerning patient care in an Intensive Car Unit (ICU) is described. Case-based reasoning offers a model for quickly matching--using a predetermined hierarchical structure--a single patient's parameters (text or numeric) to similar parameters contained in a clinical database. The output produces a group of patients which may be set to match exactly on certain characteristics and may also be set to match "as closely as possible" on a gradient of patient properties. Clinicians may thus use the system to find the group of the closest matching cases to their current patient. Aspects of the ICU history of the selected group may then be displayed graphically (e.g., mortality, length of stay, hours of ventilation, procedures utilized, and complications encountered). Neural network analysis is a pattern recognition technique which uses a training set of patient data (text or numeric) to seek mathematical relationships between various subsets of patient parameters. The discovered relationships from the training set are then applied to estimate the outcomes (e.g., mortality, length of stay, hours of ventilation) of new patients. The effects of these intelligent monitoring techniques are scheduled to be tested in a field trial held in a regional referral center ICU.