Exploring Deep Learning Methods Used in the Medical Device Sector

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Fredrick Kayusi
Benson Turyasingura
Petros Chavula
Orucho Justine Amadi

Abstract

The healthcare sector is witnessing significant development in many aspects thanks to the effects of artificial intelligence or software, which has turned out to be the centre of attraction all over the world. This is evidence of a simple development in acquiring deep knowledge of the methods and areas in which they are used. Face detection, voice recognition, autonomous use, the defence industry, the security industry, and other fields may be displayed as examples that help complete tasks. This article surveys the impact of deep learning methods and practices in the medical device industry, and we also examine the distribution of multi-year data. It is divided into six categories: healthcare, big data and wearable technologies, biomedical code, image processing, diagnostics, and the Internet of Medical Things. As a result, the medical device industry has grown in recent years through deep learning techniques and the use of most research related to diagnosis and image processing.

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How to Cite
Kayusi, F., Turyasingura, B., Chavula, P., & Justine Amadi, O. (2024). Exploring Deep Learning Methods Used in the Medical Device Sector. Mesopotamian Journal of Artificial Intelligence in Healthcare, 2024, 42–49. https://doi.org/10.58496/MJAIH/2024/007
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