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Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/8021
Title: Mejora diagnóstica de hepatopatías de afectación difusa mediante técnicas de inteligencia artificial
Authors: Perez-Poch, Antoni
Director: Delgado Pin, Jordi
Other: Universitat Oberta de Catalunya
Keywords: ultrasonography
diffuse hepatopathies
artificial intelligence
Fuzzy k-Means
machine learning
Issue Date: 24-Jun-2011
Publisher: Universitat Oberta de Catalunya
Type: Bachelor Thesis
Abstract: The automatic diagnostic discrimination is an application of artificial intelligence techniques that can solve clinical cases based on imaging. Diffuse liver diseases are diseases of wide prominence in the population and insidious course, yet early in its progression. Early and effective diagnosis is necessary because many of these diseases progress to cirrhosis and liver cancer. The usual technique of choice for accurate diagnosis is liver biopsy, an invasive and not without incompatibilities one. It is proposed in this project an alternative non-invasive and free of contraindications method based on liver ultrasonography. The images are digitized and then analyzed using statistical techniques and analysis of texture. The results are validated from the pathology report. Finally, we apply artificial intelligence techniques as Fuzzy k-Means or Support Vector Machines and compare its significance to the analysis Statistics and the report of the clinician. The results show that this technique is significantly valid and a promising alternative as a noninvasive diagnostic chronic liver disease from diffuse involvement. Artificial Intelligence classifying techniques significantly improve the diagnosing discrimination compared to other statistics.
Language: Spanish
URI: http://hdl.handle.net/10609/8021
Appears in Collections:Bachelor thesis, research projects, etc.


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