2014
Santiago-Mozos, Ricardo; Perez-Cruz, Fernando; Madden, Michael; Artés-Rodríguez, Antonio
An Automated Screening System for Tuberculosis Artículo de revista
En: IEEE journal of biomedical and health informatics, vol. 18, no 3, pp. 855-862, 2014, ISSN: 2168-2208.
Resumen | Enlaces | BibTeX | Etiquetas: Automated screening, Bayesian, Decision making, Sequential analysis, Tuberculosis
@article{Santiago-Mozos2013,
title = {An Automated Screening System for Tuberculosis},
author = {Ricardo Santiago-Mozos and Fernando Perez-Cruz and Michael Madden and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.tsc.uc3m.es/~antonio/papers/P47_2014_An Automated Screening System for Tuberculosis.pdf http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6630069},
issn = {2168-2208},
year = {2014},
date = {2014-05-01},
journal = {IEEE journal of biomedical and health informatics},
volume = {18},
number = {3},
pages = {855-862},
publisher = {IEEE},
abstract = {Automated screening systems are commonly used to detect some agent in a sample and take a global decision about the subject (e.g. ill/healthy) based on these detections. We propose a Bayesian methodology for taking decisions in (sequential) screening systems that considers the false alarm rate of the detector. Our approach assesses the quality of its decisions and provides lower bounds on the achievable performance of the screening system from the training data. In addition, we develop a complete screening system for sputum smears in tuberculosis diagnosis, and show, using a real-world database, the advantages of the proposed framework when compared to the commonly used count detections and threshold approach.},
keywords = {Automated screening, Bayesian, Decision making, Sequential analysis, Tuberculosis},
pubstate = {published},
tppubtype = {article}
}
2008
Santiago-Mozos, Ricardo; Fernandez-Lorenzana, R; Perez-Cruz, Fernando; Artés-Rodríguez, Antonio
On the Uncertainty in Sequential Hypothesis Testing Proceedings Article
En: 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 1223–1226, IEEE, Paris, 2008, ISBN: 978-1-4244-2002-5.
Resumen | Enlaces | BibTeX | Etiquetas: binary hypothesis test, Biomedical imaging, Detectors, H infinity control, likelihood ratio, Medical diagnostic imaging, medical image application, medical image processing, Medical tests, patient diagnosis, Probability, Random variables, Sequential analysis, sequential hypothesis testing, sequential probability ratio test, Signal processing, Testing, tuberculosis diagnosis, Uncertainty
@inproceedings{Santiago-Mozos2008,
title = {On the Uncertainty in Sequential Hypothesis Testing},
author = {Ricardo Santiago-Mozos and R Fernandez-Lorenzana and Fernando Perez-Cruz and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4541223},
isbn = {978-1-4244-2002-5},
year = {2008},
date = {2008-01-01},
booktitle = {2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro},
pages = {1223--1226},
publisher = {IEEE},
address = {Paris},
abstract = {We consider the problem of sequential hypothesis testing when the exact pdfs are not known but instead a set of iid samples are used to describe the hypotheses. We modify the classical test by introducing a likelihood ratio interval which accommodates the uncertainty in the pdfs. The test finishes when the whole likelihood ratio interval crosses one of the thresholds and reduces to the classical test as the number of samples to describe the hypotheses tend to infinity. We illustrate the performance of this test in a medical image application related to tuberculosis diagnosis. We show in this example how the test confidence level can be accurately determined.},
keywords = {binary hypothesis test, Biomedical imaging, Detectors, H infinity control, likelihood ratio, Medical diagnostic imaging, medical image application, medical image processing, Medical tests, patient diagnosis, Probability, Random variables, Sequential analysis, sequential hypothesis testing, sequential probability ratio test, Signal processing, Testing, tuberculosis diagnosis, Uncertainty},
pubstate = {published},
tppubtype = {inproceedings}
}