作为人工智能训练数据集的肺结核痰样本图像存储数据库系统

H. H. Muljo, A. S. Perbangsa, T. W. Cenggoro, Kartika Purwandari, D. Sudigyo, B. Pardamean
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引用次数: 2

摘要

印度尼西亚结核病的高流行率使印度尼西亚成为继印度之后世界上结核病流行率第二高的国家。这种高流行率可能导致无法向结核病患者提供治疗,而印度尼西亚医生分布不均又加剧了这种情况。为了解决这个问题,需要一个人工智能系统来帮助医生在短时间内对大量患者进行筛查。然而,为了开发一个强大的人工智能,我们需要一个大的数据集。本研究旨在开发一个用于存储结核病痰样本图像的数据库系统,并将其作为训练结核病检测人工智能的数据集。开发的系统可以帮助医生和卫生工作者在日常工作中管理图像。经过一段时间后,存储的图像可以作为训练AI的数据集。
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Database System for Storing Tuberculosis Sputum Sample Images as an AI Training Dataset
The high prevalence of Tuberculosis (TB) in Indonesia puts Indonesia in the second-highest national TB prevalence in the world after India. This high prevalence can cause a failure to deliver medical treatments to TB patients, which is exacerbated by the disproportionate distribution of doctors in Indonesia. To address this issue, an AI system is necessary to help doctors in screening a large number of patients in a short time. However, to develop a robust AI for this purpose, we need a large dataset. This study aims to develop a database system for storing TB sputum sample images, which can be used as the dataset to train an AI for TB detection. The developed system can help doctors and health workers to manage the images during their daily job. After a period of time, the stored images can be utilized as the dataset to train AI.
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