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Keith Reemtsma, MD; Richard D. Yoder, MD; Edward S. Lindsey, MD

JAMA. 1966;196(11):983-984.

	Since this article does not have an abstract, we have provided the first 150 words of the full text PDF and any section headings.

Renal transplantation offers unique opportunities in the development of automated methods of data processing. Various groups working in renal transplantation use similar methods in selection, evaluation, and treatment of cases, thereby simplifying development of standard forms for data reporting. Furthermore, the large amount of data accumulated in these cases is difficult to analyze by standard methods.

Full and prompt sharing of research information is a long-recognized and widely accepted goal in the scientific community. Complexities of biomedical research and limitations of communications, however, often preclude such sharing. By traditional methods, each investigator collects data, interprets results, and presents this information if, when, and how he chooses. A delay between accumulation of data and publication or presentation thus is inevitable. In some areas of medical research these delays are relatively unimportant or even desirable, as is the case, for example, when results are assessed in such terms as 5-year or 20-year . . . [Full Text PDF of this Article]

Author Affiliations
From the Department of Surgery (Drs. Reemtsma and Lindsey) and the Division of Medical Computing Sciences (Dr. Yoder), Tulane University School of Medicine, New Orleans.

Footnotes
Reprint requests to 1430 Tulane Ave, New Orleans 70112 (Dr. Reemtsma).

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