Automated medical diagnosis with fuzzy stochastic models: Monitoring chronic diseases

Acta Biotheoretica 52 (4):291-311 (2004)
  Copy   BIBTEX

Abstract

As the world population ages, the patients per physician ratio keeps on increasing. This is even more important in the domain of chronic pathologies where people are usually monitored for years and need regular consultations.To address this problem, we propose an automated system to monitor a patient population, detecting anomalies in instantaneous data and in their temporal evolution, so that it could alert physicians. By handling the population of healthy patients autonomously and by drawing the physicians' attention to the patients–at-risk, the system allows physicians to spend comparatively more time with patients who need their services. In such a system, the interaction between the patients, the diagnosis module, and the physicians is very important. We have based this system on a combination of stochastic models, fuzzy filters, and strong medical semantics.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 94,070

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Physicians Have a Responsibility to Meet the Health Care Needs of Society.Allan S. Brett - 2012 - Journal of Law, Medicine and Ethics 40 (3):526-531.
Truth-telling and patient diagnoses.R. J. Sullivan - 2001 - Journal of Medical Ethics 27 (3):192-197.
Dwelling in the Shadow: Physicians' Decision-Making for Terminally Ill Patients.Stephen Vanhooser Mccrary - 1992 - Dissertation, The University of Texas Graduate School of Biomedical Sciences at Galveston

Analytics

Added to PP
2009-01-28

Downloads
27 (#578,634)

6 months
3 (#1,209,684)

Historical graph of downloads
How can I increase my downloads?

References found in this work

No references found.

Add more references