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Saeful Bahri
(Scopus Author ID: 57216680383) Universitas Muhammadiyah Jakarta
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Journal : International Journal of Advances in Intelligent Informatics

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Computer-aided pulmonary disease diagnosis using lung ultrasound video Bahri, Saeful; Suprijanto, Suprijanto; Juliastuti, Endang
International Journal of Advances in Intelligent Informatics Vol 10, No 3 (2024): August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v10i3.1397

Abstract

The development of a machine learning-based computer-aided diagnosis (CAD) system implemented for processing lung ultrasound images will greatly assist doctors in making decisions in diagnosing lung diseases. The learning method of the classifier model used in the computer-aided diagnosis system will affect the system's accuracy in diagnosing lung disease. Determining variables in the classifier and image pre-processing stages requires special attention to obtain a highly accurate classifier model. This study presents the development of a machine learning-based CAD as an add-on tool to classify lung disease based on a lung ultrasound (LUS) video. The main steps in this study are capturing the LUS videos and converting them into images, image pre-processing for speckle noise removal, image contrast and brightness enhancement, feature extraction, and the classification stage. In this study, three learning algorithm models, namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naïve Bayes (NB), were used to classify images into three categories, namely healthy conditions, pneumonia, and COVID-19.  The performance of the three classifier models is compared to each other to obtain the best classifier model. The experimental results demonstrate the superiority of the suggested strategy utilizing the SVM classifier. Based on experimental data using 2,149 lung images for three classes and 20 texture feature sets, the SVM has an accuracy of 98.1%, the KNN is 94.7%, and the Gaussian NB is 79.6%. The model with the highest accuracy will be used to develop the computer-aided diagnosis (CAD) system.
Co-Authors Achmad Fauzi Agus Sutisna Agus Yulianto Ahmad Nur Faizin Ahmad Yusuf Al Zahra, Nabila Al-Amin, Roby Andhika Darmawan Andi Riyanto Andi Zulfa Majida Andia Ridho Arif Anggraini, Recha Abriana Anisa Anisa Arafah, Sitti Ari Widyati Purwantiasning Ari Widyati Purwantiasning Arief, Dasya As. Rakhmad Idris, As. Rakhmad Asep Saefullah Ashadi Buana, Muhammad Cakra Chairul Anwar Dede Burhanudin, Dede Dede Wintana Eka Ratna Safitri Endang Juliastuti Erwin Dermawan Fadillah Rezky, Syarifah Fadliondi Faris, Nahrul Febby Angga Permana, Febby Angga Fikriyah, Kholisotu Giriana, Dewinta Firda Gunawan Gunawan Gunawan Hardivizon Hardivizon Haris Isyanto Heri Kusindaryadi Husnibes Muchtar Husnibes Muchtar Ilham, Muhammad Faris Iqbal Fadhilah Jahdiah Jahdiah, Jahdiah Jihan Sonia Khaerurani Nur Asyifa Koeswara, Tya Septiani Nurfauziah Kokom Komariah Kumala Sari, Eva Dwi Kusmira, Mira Kuswandi, Irwan Mahmudah Nur, Mahmudah Masitoh, Rikha Masyitoh Melisa Winda Pertiwi Miftahul Janah Mochamad Noorman Bayuardi Moh.Badrul Alam Muhamad Rosadi, Muhamad Muhammad Akbar Rafsyanjani Muhammad Cakra Buana Muhammad Fachri Baharsyah Muhammad Hidayat Nur Wahid Muhammad Miftahussalam Musyfikah Ilyas, Musyfikah Mutawakkil, Muhammad Pasya Nanda Alifia Nasruhi, Moch. Nugraha, Setyo Bagus Nur'aini, Yusna Salma Nuraini, Yusna Salma Nurohmah, Siti Nursugiharti, Titih Pangestu, Agis Panggalih Sako Denta Pindha Kaptiningrum Pribadi, Denny Purwono Purwono Putra Arista Pratama, Putra Putra Septia Yuza Qur'ani, Tsaura Halwa Rafsyanjani, Muhammad Akbar Ratningsih, Ratningsih Ridwan ridwan Riza Samsinar Rizal Amegia Saputra Rizka Amalia Roch Aris Hidayat, Roch Aris Rusda Wajhillah, Rusda Ruslan Abdul Gani Safei, Mawar Satia Suhada, Satia Setiawan, Sandy Sinta Nur Hilali Sinuraya, Junus SITI KHOLIFAH Sri Endah Wahyuningsih Sri Wuli Fitriati Stefani Kusuma Dewi Suhardiyanto Suhardiyanto, Suhardiyanto Sulaeman, Hamdun Sumarno, Ardawi Suprijanto Suprijanto Sururi Syibromalisi, Arif Taufik Hidayatulloh Tuffahati, Wafa W, Widhiyanto Wardany, Mutia Setya Widayati Widhiyanto Yanti Apriyani, Yanti Yogi Haryono Yulianto Yuri Rahayu Ziaul Fiqih, Ziaul