Systematic Literature Review pada Penggunaan Deep Learning untuk Deteksi Dini Penyakit

Abdul Rahman; Riyayatsyah Riyayatsyah

doi:10.56861/cognitech.v1i1.8

Authors

Abdul Rahman Universitas Salakanagara
Riyayatsyah Riyayatsyah Universitas Mulia

DOI:

https://doi.org/10.56861/cognitech.v1i1.8

Keywords:

Deep learning, deteksi dini penyakit, citra medis, kecerdasan buatan, sistem kesehatan digital, early disease detection, medical imaging, artificial intelligence, digital healthcare systems

Abstract

Advances in artificial intelligence technology, particularly deep learning, have driven major transformations in early disease detection. With the ability to analyze large amounts of medical data, deep learning algorithms can accurately and efficiently identify complex patterns in medical images, electronic health records, and biological signals. This study is a systematic literature review that aims to summarize the latest developments in the use of deep learning for the early detection of various types of diseases. Based on a rigorous selection of 590 articles from four major databases, 10 studies were selected for in-depth analysis. The main findings show that deep learning has been successfully applied to the detection of lung, neurological, cardiovascular, and sleep disorders. Models such as CNN, RNN, and hybrid architectures show high performance in medical data-based classification and diagnosis. However, challenges arise, including the limited availability of high-quality data, computational complexity, and the need for clinical validation. The results of this study emphasize that the integration of deep learning technology into healthcare systems not only improves the accuracy and efficiency of diagnosis but also opens up great opportunities for predictive and personalized healthcare services. This research emphasizes the need to strengthen data infrastructure, multimodal approaches, and synergy between technology and medical personnel as the foundation for optimizing the role of deep learning in modern healthcare systems.

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