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PubMed2001

Theory and practice in epidemiology.

Scientific and ethical theories are examined in terms of the practice of epidemiology, the study of the determinants and distributions of disease, and the application of the knowledge gained to prevent disease and improve the health of populations. Scientific theories provide explanations and predictions for epidemiologic studies of disease etiology and prevention. Causal theory is the key example for epidemiologic science, although theories of selection processes, theories of health, and theories of probability and statistics are also core. Theories of ethics provide principles, warrants, and methods for acting upon the knowledge gained in the scientific pursuits of epidemiology and for obtaining that knowledge appropriately. Ethical theories guide practitioners in making justified decisions about when and under what conditions public health interventions should be undertaken and how research participants should be treated. Theories of midlevel bioethical principles have received the most attention in epidemiology, but other theories, such as virtue theory and communitarian theory, are also relevant. Many theories matter to the practice of epidemiology: theories of biology, aging, evolution, and medicine; theories of history, religion, law, economics, and politics, as well as the theories of the physical, behavioral, and social sciences. These theories matter because epidemiologists study many different biological and social phenomena, and preventive interventions occur at many different levels of explanation. Development of theory is not a high priority in contemporary epidemiology. Identifying the responsibilities of the discipline to be public health intervention and rigorous science is a first step toward developing and applying theory in epidemiology.

Causality↗
PubMed1977

[Perspectives of using the probability principles for the study of the problems of normal and pathological morphology].

On the literature available and the author's data the prospects on application of probability principles for the study of certain problems of normal and pathological morphology are discussed. Short consideration is given from the theory of probability and information with theoretical grounds for their possible application in morphology. From this standpoint some problems of morphological bases of homeostasis, adaptation, compensation and pathological processes are reviewed. Certain points of the probability theory of atherosclerotic morphogenesis and informative characteristic of malignization in stratified epithelium of laryngeal mucosa illustrate the article. General principles for further development of quantitative morphology are shortly elucidated.

Age Factors↗
PubMedDate not supplied

A new classifier based on information theoretic learning with unlabeled data.

Supervised learning is conventionally performed with pairwise input-output labeled data. After the training procedure, the adaptive system's weights are fixed while the testing procedure with unlabeled data is performed. Recently, in an attempt to improve classification performance unlabeled data has been exploited in the machine learning community. In this paper, we present an information theoretic learning (ITL) approach based on density divergence minimization to obtain an extended training algorithm using unlabeled data during the testing. The method uses a boosting-like algorithm with an ITL based cost function. Preliminary simulations suggest that the method has the potential to improve the performance of classifiers in the application phase.

Algorithms↗
PubMedDate not supplied

[Theory of kinetic schemes. Random walks].

During special selection of self--functions of states methods of the kinetic scheme theory can be extrapolated on some probability processes. General solutions can be obtained with these methods, for the problem of casual wanderings in manymeric lattices for example. The general result of the work--distribution of average lifetime of a population in states is in the general case determined only by the topology of the scheme and is independent of the form of self-functions of states.

Kinetics↗
PubMed1994

Certainty and uncertainty in science: the subjectivistic concept of probability in physiology and medicine.

Most physiological scientists have restricted understanding of probability as relative frequency in a large collection (for example, of atoms). Most appropriate for the relatively circumscribed problems of the physical sciences, this understanding of probability as a physical property has conveyed the widespread impression that the "proper" statistical "method" can eliminate uncertainty by determining the "correct" frequency or frequency distribution. However, many relatively recent developments in the theory of probability and decision making deny such exalted statistical ability. Proponents of Bayes's subjectivist theory, for example, assert that probability is "degree of belief," a more tentative idea than relative frequency or physical probability, even though degree of belief assessment may utilize frequency information. In the subjectivist view, probability and statistics are means of expressing a consistent opinion (a probability) to handle uncertainty but never means to eliminate it. In the physiological sciences the contrast between the two views is critical, because problems dealt with are generally more complex than those of physics, requiring judgments and decisions. We illustrate this in testing the efficacy of penicillin by showing how the physical probability method of "hypothesis testing" may contribute to the erroneous idea that science consists of "verified truths" or "conclusive evidence" and how this impression is avoided in subjectivist probability analysis.

Bayes Theorem↗