Lung cancer. Difference in age at diagnosis between men and women.

The analysis of a data file comprising 776 lung cancer patients from the Tumor Registry at a 705-bed community hospital in New Jersey reveals that women are diagnosed with squamous cell and large cell lung cancer at an earlier age than men.

The role of modeling methods in medical diagnosis.

Modeling methods in medical diagnosis are concerned with medical information processing as it pertains to utilizing biological modeling methods to facilitate patient care. Major considerations in this particular area are (1) the classification problem related to the establishment of disease entities-the taxonomy problem, and (2) the diagnosis of diseases. Available are properties, criteria, signs, symptoms, and manifestations of diseases that have been cumulated and categorized by clinicians and researchers. The problem is to optimally utilize the information content of a sign or set of signs in the practice of patient care as pertaining to the medical diagnosis problem. Some mathematical approaches implemented to facilitate such analyses include cluster analysis, discriminant analysis, Bayesian methods, computer approaches, game theory, information theory, stochastic representations, stepwise procedures, decision analysis, and pattern recognition techniques. Each of these has been studied in depth by numerous researchers advocating computer applications in medicine. Here we discuss the scope and limitations of utilizing modeling methods as a viable approach to interpreting vast amounts of biological data collected on a single patient during an encounter. We consider the following: (1) limitations associated with modeling methodologies; (2) levels of responsibilities, ranging over logging, summarizing, reporting, monitoring, and therapy selection; and (3) operational strategies and considerations as they affect hardware logistics, the actual algorithm utilized, and implementation of these sophisticated analysis systems.