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Natalia Satya, Putri Gabriella Angel
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Health Professions Medicine & Pharmacology Public Health

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Journal : Cermin Dunia Kedokteran

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Revolution in Detecting Tuberculosis using Radiology with Application of Deep Learning Algorithm Natalia Satya, Putri Gabriella Angel; Parikesit, Arli Aditya
Cermin Dunia Kedokteran Vol 48, No 4 (2021): Dermatologi
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (126.452 KB) | DOI: 10.55175/cdk.v48i4.1475

Abstract

Radiology is a medical examination of internal body parts using data imaging to interpret an illness. Many illnesses can be detected using this medical discipline; one of the diseases is tuberculosis caused by Mycobacterium tuberculosis bacteria. The supreme ability of Artificial Intelligence and Machine learning has amazed the radiologist in analyzing big data-based information. A better deep learning algorithm can lead radiologist to accurate results. This article will review ten (10) research papers that use a deep learning algorithm in the application to detect tuberculosis by data processing technique. The goal is to know the best type of data processing in deep learning to detect TB.Radiologi adalah pemeriksaan bagian dalam tubuh menggunakan data pencitraan untuk interpretasi suatu penyakit. Banyak penyakit dapat dideteksi menggunakan disiplin medis ini; salah satu adalah tuberkulosis yang disebabkan oleh bakteri Mycobacterium tuberculosis yang menyerang paru-paru. Ahli radiologi tertarik atas kemampuan Artificial Intelligence dan Machine Learning untuk analisis data yang akurat. Artikel ini akan mengulas sepuluh (10) makalah penelitian aplikasi algoritma deep learning untuk deteksi tuberkulosis menggunakan teknik pengolahan data.
Co-Authors Arli Aditya Parikesit