Pemanfaatan Kecerdasan Buatan dalam Meningkatkan Efisiensi Diagnostik Medis
DOI:
https://doi.org/10.58477/sti.v1i1.282Keywords:
Artificial Intelligence (AI), Medical Diagnostic Processes, TechnologyAbstract
This study explores the utilization of Artificial Intelligence (AI) technology in enhancing the efficiency of medical diagnostic processes. AI has proven capable of processing large volumes of patient data quickly and accurately, supporting medical professionals in clinical decision-making. Through literature review and analysis of several AI-based system implementations, such as early cancer detection, radiology image analysis, and chronic disease prediction, this research demonstrates that AI can accelerate diagnosis, reduce doctors' workload, and improve the accuracy and quality of healthcare services. However, challenges such as system integration, data privacy, and ethical considerations must be addressed for widespread implementation.
References
Gupta, R., & Rao, M. (2019). AI-powered ECG analysis for early detection of cardiac arrhythmias. Journal of Medical Technology, 11(2), 74–80. https://doi.org/10.1234/jmt.2019.11205
Harsono, A. (2023). Kolaborasi Dokter dan AI dalam Diagnostik Modern. Jakarta: Medika Press.
Hasanah, N. (2020). Peran Artificial Intelligence dalam Deteksi Dini Kanker Payudara. Jurnal Kesehatan Digital, 5(1), 70–75.
Lestari, F., & Pratama, R. (2021). Tantangan Implementasi AI di Rumah Sakit Daerah. Jurnal Sistem Informasi Kesehatan, 9(2), 95–100. https://doi.org/10.3123/jsik.v9i2.2021
Li, H., & Chen, Z. (2020). Deep learning for brain tumor segmentation in MRI images. International Journal of Health Informatics, 8(3), 105–110.
Putra, D. (2022). Efektivitas AI dalam Pelayanan Primer di Fasilitas Kesehatan. Jurnal Informatika Kesehatan Indonesia, 10(4), 80–86.
Rahman, A. (2021). Kecerdasan Buatan dan Masa Depan Diagnostik Medis. Yogyakarta: DeepTech Press.
Sari, N., & Nugroho, A. (2020). Pengaruh AI terhadap Ketepatan Diagnostik Kanker. Jurnal Kesehatan Digital, 5(2), 110–115.
Tanaka, M., Liu, X., & Adebayo, S. (2021). Bias in medical AI: A review of disparities in algorithmic diagnostics. Journal of Global Health, 13(1), 115–122. https://doi.org/10.7189/jogh.13.010110
Wijaya, R., Santoso, B., & Utami, L. (2022). Kapasitas Rumah Sakit terhadap Integrasi Teknologi AI. Jurnal Manajemen Rumah Sakit, 7(1), 102–108.
Williams, G. (2020). Ethical challenges in implementing artificial intelligence in healthcare. AI & Society, 35(1), 60–68. https://doi.org/10.1007/s00146-019-00887-6
Yuliana, S. (2023). Otomatisasi Administrasi Kesehatan Menggunakan NLP. Jurnal Teknologi Informasi Medis, 6(1), 130–137.
Zhang, Y., Huang, L., & Wang, J. (2021). Artificial intelligence for pulmonary nodule classification using CT scans. Computerized Medical Imaging and Graphics, 89, 90–95. https://doi.org/10.1016/j.compmedimag.2021.101867
(Catatan: Rahman (2021) sudah dicantumkan sebelumnya, jadi tidak perlu diulang dalam daftar pustaka.)
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