Optimizing the Display and Interpretation of Data
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"What information do these data reveal?" "Is the information correct?" "How can I make the best use of the information?" The widespread use of computers and our reliance on the data generated by them have made these questions increasingly common and important. Computerized data may be in either digital or analog form and may be relevant to a wide range of applications that include medical monitoring and diagnosis, scientific research, engineering, quality control, seismology, meteorology, political and economic analysis and business and personal financial applications. The sources of the data may be databases that have been developed for specific purposes or may be of more general interest and include those that are accessible on the Internet.
In addition, the data may represent either single or multiple parameters. Examining data in its initial form is often very laborious and also makes it possible to "miss the forest for the trees" by failing to notice patterns in the data that are not readily apparent. To address these problems, this monograph describes several accurate and efficient methods for displaying, reviewing and analyzing digital and analog data. The methods may be used either singly or in various combinations to maximize the value of the data to those for whom it is relevant. None of the methods requires special devices and each can be used on common platforms such as personal computers, tablets and smart phones. Also, each of the methods can be easily employed utilizing widely available off-the-shelf software.
Using the methods does not require special expertise in computer science or technology, graphical design or statistical analysis. The usefulness and accuracy of all the described methods of data display, review and interpretation have been confirmed in multiple carefully performed studies using independent, objective endpoints. These studies and their results are described in the monograph. Because of their ease of use, accuracy and efficiency, the methods for displaying, reviewing and analyzing data described in this monograph can be highly useful to all who must work with computerized information and make decisions based upon it.
Warner, Robert: - Robert A. Warner, MD is board-certified in both Internal Medicine and Cardiology and is currently living and working near Portland, Oregon. He received his BS degree from Union College in 1964 and his MD degree from Upstate Medical Center in 1969. He completed a residency in internal medicine at Upstate in 1972 and a fellowship in cardiology at Duke University Medical Center in 1975. He was an Eliphalet Nott Scholar at Union College and is a member of the Phi Beta Kappa, Sigma Xi and Alpha Omega Alpha honor societies. Dr. Warner was a member of the faculty of Upstate Medical Center College of Medicine from 1975 to 1998 where he rose to the rank of Full Professor of Medicine. From 1986 to 1996, he served as Chief of the Medical Service at the Syracuse VA Medical Center. From 1998 to 2002, Dr. Warner did medical research at the Duke University Clinical Research Institute in Durham, North Carolina and from 2002 to 2006 served as the Medical Director of Inovise Medical, Inc. in Portland, Oregon. Since then, he has remained active in research, continues to publish in medical and computer science journals and frequently presents his research findings at scientific meetings. Most of his current work consists of improving the accuracy of medical diagnoses and optimizing the interpretation of computer-generated data. The methods of interpretation that he has developed apply not only to biomedical data, but are also relevant to such diverse fields as engineering, the physical and social sciences, business and personal finance. Dr. Warner is the author of over 75 papers and 95 abstracts that have been published in peer-reviewed journals. He has served as consultant to many companies in the medical device and pharmaceutical industries and is the holder of four patents that are all related to the display and interpretation of biomedical data.
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