Kinerja kecerdasan buatan dalam mendeteksi fraktur tulang pada hasil radiografi : Sistematik Literatur Review
DOI: https://doi.org/10.56922/msc.v4i2.689
AI CT Scan Kecerdasan Buatan MRI Radiologi X- Ray
Abstract
Abstract
Background: artificial intelligence (AI), is currently very widely used in various lines of human life, including in the health sector. Dalam ilmu radiologi peran AI sudah mulai dilibatkan dalam interpretasi pembacaan hasil pencitraan radiologi dengan tujuan agar penegakana diagnosis radiologis dapat berjalan lebih efisien.
Purpose: To assess the performance of artificial intelligence in detecting human bone fractures on rediological imaging results.
Method: A systematic literature review method using the PUBMED search application with a publication time span of the last 5 years using search queries ("artificial intelligence" OR "machine learning" OR "deep learning") AND ("bone fracture detection" OR "fracture detection" OR "bone injury detection") AND ("X-ray" OR "radiograph") AND ("sensitivity" OR "diagnosis speed "OR" cost efficency).
Result: The results of the search found 27 manuscripts that were included in the inclusion criteria, where it can be seen that the use of AI in the field of radiology has been carried out in many countries, not only for x-ray radiology imaging, but also for CT Scan, and MRI imaging, which are applied to various bone fractures and have also been compared in speed and effectiveness for diagnosis using human radiologists.
Conclusion: From this study, it can be concluded that the artificial intelligence method has a fairly good ability in identifying human bone fractures on radiological images, which can help clinicians to avoid misdiagnosis and speed up the time to establish the diagnosis.
Pendahuluan: Kecerdasan buatan atau yang sering dikenal dengan artificial inteligent (AI), saat ini sudah sangat luas sekali digunakan dalam berbagai lini kehidupan manusia, termasuk di bidang kesehatan. Dalam ilmu radiologi peran AI sudah mulai dilibatkan dalam interpretasi pembacaan hasil pencitraan radiologi dengan tujuan agar penegakana diagnosis radiologis dapat berjalan lebih efisien.
Tujuan: Penelitian ini bertujuan untuk menilai kinerja kecerdasan buatan dalam mendeteksi fraktur tulang manusia pada hasil pencitraan radilogis.
Metode: Studi ini dilakukan dengan metode sistematik literatur review menggunakan aplikasi pencarian PUBMED dengan rentang waktu publikasi 5 tahun terakhir menggunakan query pencarian ("artificial intelligence" OR "machine learning" OR "deep learning") AND ("bone fracture detection" OR "fracture detection" OR "bone injury detection") AND ("X-ray" OR "radiograph") AND ("sensitivity" OR "diagnosis speed “OR” cost efficency”).
Hasil: Hasil penelusuran ditemukan 27 naskah yang masuk dalam kriteria inklusi, dimana terlihat bahwa penggunaan AI dalam bidang radiologi sudah dilakukan di banyak negara, tidak hanya untuk pencitraan radiologi x ray, namun juga pada pencitraan CT Scan, dan MRI, yang diaplikasikan pada berbagai fraktur tulang serta telah pula dilakukan perbandingan kecepatan dan efektifitasnya terhadap diagnosis menggunakan radiolog manusia.
Simpulan: Dari studi ini dapat disimpulkan bahwa metode kecerdasan buatan memiliki kemampuan yang cukup baik dalam melakukan identifikasi fraktur tulang manusia pada gambaran radiologik, hal ini dapat membantu klinisi untuk menghindari kesalahan diagnosis dan mempercepat waktu penegakan diagnosis.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
