6533b7d0fe1ef96bd125af6f

RESEARCH PRODUCT

A Novel Expert System for Non-Invasive Liver Iron Overload Estimation in Thalassemic Patients

Emanuele GrassedonioMaria Antonietta RussoMassimo MidiriPatrizia ToiaLuca AgnelloSalvatore VitabileAlfonso FarruggiaElena Murmura

subject

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniLiver Iron ConcentrationMean squared errorArtificial neural networkComputer scienceRemote patient monitoringbusiness.industryComputational intelligenceComplex problem solvingcomputer.software_genreExpert systemLIOMOT MRI T2* Iron Liver Thalassemia Artificial Neural Network Expert System OsiriXLiver ironArtificial intelligenceData miningbusinesscomputer

description

Expert Systems can integrate logic based often on computational intelligence methods and they are used in complex problem solving. In this work an Expert System for classifying liver iron concentration in thalassemic patients is presented. In this work, an ANN is used to validate the output of the L.I.O.MO.T (Liver Iron Overload Monitoring in Thalassemia) method against the output of the state-of-the-art method based on MRI T2 assessment for liver iron concentration. The model has been validated with a dataset of 200 samples. The experimental Mean Squared Error results and Correlation show interesting performances. The proposed algorithm has been developed as a plug in for OsiriX Dicom Viewer.

yearjournalcountryeditionlanguage
2014-07-01
10.1109/cisis.2014.16http://hdl.handle.net/10447/100574