ACADSTAFF UGM

CREATION
Title : Machine Learning Model for Umbilical Cord Classification Using Combination Coiling Index and Texture Feature Based On 2-D Doppler Ultrasound Images
Author :

GEDE ANGGA PRADIPTA (1) Prof. Drs. Retantyo Wardoyo, M.Sc., Ph.D. (2) Aina Musdholifah, S.Kom., M.Kom. Ph.D (3) Dr. dr. I Nyoman Hariyasa Sanjaya, SpOG(K), MARS (4)
Date : 9 2022
Keyword : Umbilical cord,Machine learning,imbalanced data sets,Multiclassifier,SMOTE. Umbilical cord,Machine learning,imbalanced data sets,Multiclassifier,SMOTE.
Abstract : The umbilical cord is an organ that circulates oxygen and nutrition from mother to fetus during pregnancy. This study aims to classify the umbilical cord based on ultrasound images. The similarity of shape and coil between each class becomes a challenge. Therefore, it requires feature values that are relevant to the characteristics of these three classes. The condition of imbalanced data sets in this study is also an obstacle that causes the classifier's performance to degrade on minority classes. Therefore, this study proposes a machine learning model capable of properly dealing with imbalanced data sets and recognizing the umbilical cord class. Furthermore, this study proposes a new feature extraction method, namely the umbilical coiling index (UCI), which directly adopts obstetricians' knowledge. The proposed model consists of five stages: image preprocessing, feature extraction, feature selection, oversampling data using SMOTE, and Classification. Machine learning method observations were carried out comprehensively on five based classifiers: Random Forest, KNN, Decision tree, SVM, Naïve Bayes, and Multiclassifier. The results showed that the Random forest and Multiclassifier methods provide the highest accuracy, precision, recall, and F-measure performance in imbalanced data sets.
Group of Knowledge : Ilmu Komputer
Original Language : English
Level : Internasional
Status :
Published
Document
No Title Document Type Action
1 Paper HIJ GAP RW AM IMHJ.pdf
Document Type : [PAK] Full Dokumen
[PAK] Full Dokumen View
2 Machine learning model for umbilical cord classification using combination coiling index and texture feature based on 2-D Doppler ultrasound images.pdf
Document Type : [PAK] Cek Similarity
[PAK] Cek Similarity View
3 Bukti Korespondensi HIJ.pdf
Document Type : [PAK] Bukti Korespondensi Penulis
[PAK] Bukti Korespondensi Penulis View
4 Surat Pernyataan Paper melibatkan mahasiswa- Gede Angga Pradipta- HIJ signed RW.pdf
Document Type : Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian)
Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian) View