Altering physiological networks using drugs: steps towards personalized physiology.

Background: The rise of personalized medicine has reminded us that each patient must be treated as an individual. One factor in making treatment decisions is the physiological state of each patient, but definitions of relevant states and methods to visualize state-related physiologic changes are scarce. We constructed correlation networks from physiologic data to demonstrate changes associated with pressor use in the intensive care unit.

Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis.

Introduction: Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult.

Infection in the intensive care unit alters physiological networks.

Background: Physicians use clinical and physiological data to treat patients every day, and it is essential for treating a patient appropriately. However, medical sources of clinical physiological data are only now starting to find use in bioinformatics research.

Results: We collected 29 types of physiological and clinical data on a minute-by-minute basis from trauma patients in the intensive care unit along with whether they contracted an infection during their stay.

A probabilistic algorithm for estimating the intention of computer users with movement disorders.

Standard computer interfaces are inefficient for many users who have movement disorders. We believe this stems from the standard view that interface devices accurately represent the intention of the user. For those who have movement disorders, such as dystonia, it may be more effective to view the computer interface as an instrument used to estimate the user's intent.