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All Journal The Indonesian Journal of Computer Science
Abdi, Abdo
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Computer Science & IT Electrical & Electronics Engineering Engineering

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OCT Images Diagnosis Based on Deep Learning – A Review Abdi, Abdo; Abdulazeez, Adnan Mohsin
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3731

Abstract

The recent advancements in deep learning technology have significantly transformed the field of medical imaging, namely in the diagnosis of ocular illnesses. The progress made in this field has improved the capacity to extract and evaluate intricate characteristics in images, with Optical Coherence Tomography (OCT) playing a crucial role. OCT has become known for its safe qualities and its high level of detail, rendering it an essential instrument in the diagnosis of eye diseases. The interesting improvement in research is centered around the integration of deep learning with OCT for the purpose of automating the detection of eye diseases. We conducted a comprehensive study that explores several diagnostic methods and the wide-ranging uses of OCT. Additionally, it addresses the accessibility of publicly available datasets that are specifically tailored to optical coherence tomography (OCT). The paper provides a detailed review of the most recent advancements in computer-assisted diagnostic methods for diseases of the eye, such as age-related macular degeneration, glaucoma, and diabetic macular edema, with a particular focus on the effective use of OCT. Moreover, the paper systematically analyzes the primary challenges that deep learning faces in OCT image interpretation, emphasizing the intricate nature and possibilities of this field.
Embracing Distributed Systems for Efficient Cloud Resource Management: A Review of Techniques and Methodologies Abdi, Abdo; Zeebaree, Subhi R. M.
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3806

Abstract

The development of parallel computing, distributed computing, and grid computing has introduced a new computing model, combining elements of grid, public computing, and SaaS. Cloud computing, a key component of this model, assigns computing to distributed computers rather than local computers or remote servers. Research papers from 2017 to 2023 provide an overview of the advancements and challenges in cloud computing and distributed systems, focusing on resource management and the integration of advanced technologies like machine learning, AI-centric strategies, and fuzzy meta-heuristics. These studies aim to improve operational efficiency, scalability, and adaptability in cloud environments, focusing on energy efficiency and cost reduction. However, these advancements also present challenges, such as implementation complexity, adaptability in diverse environments, and the rapid pace of technological advancements. These issues necessitate practical, efficient, and forward-thinking solutions in real-world settings. The research conducted between 2017 and 2023 highlights the dynamic and rapidly evolving field of cloud computing and distributed systems, providing valuable guidance for ongoing and future research. This body of work serves as a crucial reference point for advancing the field and emphasizing the need for practical, efficient, and forward-thinking solutions in the ever-evolving landscape of cloud computing and distributed systems.
Co-Authors Abdulazeez, Adnan Mohsin Zeebaree, Subhi R. M.