Implementasi Attention Augmented Convolutional Networks untuk Deteksi Penyakit Covid-19 dari Gambar X-Ray Dada
Abstract
Dalam beberapa tahun terakhir, penyakit COVID-19, yang disebabkan oleh virus corona, telah menjadi masalah kesehatan yang menantang bagi masyarakat. Metode deteksi COVID-19 dengan bantuan komputer saat ini menghadapi kesulitan untuk membedakan antara COVID-19 dan pneumonia karena keduanya memiliki gejala yang sama. Karena itu, ada kebutuhan untuk mengotomatisasi dan membantu proses pendeteksian. Kemajuan terbaru dalam deep learning telah membuka jalan baru untuk memanfaatkan data pencitraan medis untuk deteksi penyakit secara otomatis. Penelitian menghasilkan peforma Attention Augmented Convolutional Networks (AACNs) yang sedikit lebih bagus (~1%), namun dinilai kurang optimal dibandingkan dengan ResNet50 sebagai baseline. Dikarenakan adanya artefak dan beragam variasi pada data yang dapat mempengaruhi mekanisme attention.
Kata kunci: covid-19, image classification, convolutional networks.
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