Computational Intelligence

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Presentation transcript:

Computational Intelligence Computational Intelligent Diagnostic System in Predicting Fetal Aneuploidies Computational Intelligence Artificial neural networks Evolutionary systems / Genetic algorithms Artificial immune systems Fuzzy systems Maternal age Previous trisomy Crown-rump length Gestational age Nuchal translucency Fetal heart rate Free ß-hCG PAPP-A Nasal bone Tricuspid flow Ductus venosus flow Christos Schizas Kypros Nicolaides Andreas Neocleous Kleanthis Neokleous Natasa Schiza Costas Neocleous FMF, University of Cyprus, Cyprus University of Technology, Cyprus

Computational Intelligent System in predicting fetal aneuploidies Objective: Employ computational intelligence to predict fetal aneuploidies Artificial Neural Network Architecture Input (10 neurons) Age, previous trisomy, CRL, NT, FHR, ß-hCG, PAPP-A, NB, TR, DV (Linear activation) Hidden Layer 1 (80 neurons) (Logistic activation) Output Layer (5 neurons) Normal / Abnormal (Turner, T13,T18,T21) Hidden Layer 2 (10 neurons) (Symmetric logistic activation) Hidden Layer 3 (80 neurons) All data: Total singleton pregnancies 34,182 Euploid 33,792 (98.8%) Aneuploidy 390 (1.2%) Trisomy 21 213 Trisomy 18 97 Trisomy 13 27 Triploidy 18 Turner syndrome 35 Data for training, simulations and validations: Training various artificial neural networks 26,000 Totally unknown cases used for validations 8,182

Computational Intelligent System in predicting fetal aneuploidies Results on the unknown validation (verification) data set: Predicted Correct ALL cases Euploid Aneuploid 8,032 64 8,017 (99.8%) 64 (100%) Classification into EUPLOID - ANEUPLOID Predicted Correct ALL cases Euploid Trisomy 21 8,032 60 8,016 (99.8%) 54 (90.0%) Classification into EUPLOID – Trisomy 21 Normal Trisomy 21 Trisomy 18 Trisomy 13 Triploidy Turner ALL cases 4,521 4,482 21 10 3 2 Predicted Correct 4,505 (99.5%) 4,481 (99.98%) 18 (85.7%) 6 (60.0%) Classification into EUPLOID - T21 – T18 - T13 – Triploidy - Turner

Computational Intelligent System in predicting fetal aneuploidies Conclusions There is a very good discrimination between Euploid and Aneuploid cases There is a good discrimination between normal and Trisomy 21 cases T13, Triploidy and Turner cases are hard to predict (mainly because of the small number of cases available for network training) Thank you