The potential for methodologic research of computer algorithms in biomedical research has been tremendously expanded recently by the increased availability of powerful computation resources. This is a request to obtain a microcomputer data file server and satellite workstations to enable investigator access to sophisticated software tools. Configured as a departmental network system, these computer resources would augment the existing administrative mainframe resource presently used by researchers in the department. A client/server workstation model would enable computationally intensive tasks to be undertaken on a significantly greater scale than we can presently afford under the mainframe CPU chargeback system. Prototypic projects that would become feasible under the proposed network include: 1. Exploratory data analysis and the validity of asymptotic results in finite samples. (Dr. H.S. Wieand) 2. Data base architecture for patient care data in health care research. (Dr. D.J. Ballard) 3) Artificial Intelligence (AI) applications to medical coding schemes. (Dr. C.G.Chute) 4. Modeling the natural history of major chronic liver diseases. (Dr.P.M. Grambsch) 5. Projected effects of population-based prevention strategies arising from simulation models. (Dr. T.E. Kottke) 6. Evaluation of stochastic disease models applied to population incidence data. (Dr. L.J. Melton) 7. Robust procedures for testing equality of covariance matrices. (Dr. P.C. O'Brien) 8. Development of biostatistical procedures for epidemiologic analysis. (Mr. K.P. Offord) 9. A--Analysis of human genetic linkage. B--Development of new designs for cancer clinical trials. (Dr. D.J. Schaid) 10. Improvements to pharmacokinetic models used in clinical research. (Dr. T.M. Therneau) 11. Linkage of disease registry data for interactive epidemiologic analysis. (Dr. J.P. Whisnant) Mayo Clinic has a long heritage of contributing to biomedical research methodology and medical knowledge. The proposed resource will enable us to continue in that tradition, and expand our contributions to areas well suited to our natural laboratory of clinical information.
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