深度学习工具和技术在肺部感染早期检测和诊断中的就业能力

Sakshi Loura
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引用次数: 0

摘要

胸部x线成像是一些危及生命的感染必不可少的筛查和药物设备;然而,由于放射科医生的缺乏,这种筛查仪器并不能治疗所有的病人。在这项研究中,我们从胸部x线图像中识别出14种不同类型的胸部感染。这项任务的主要目标是以最高的准确性了解对人体胸部进行的每14次测试的感染识别水平。基于深度学习的医学图像分类器是一种预期的反应。同样,它在进行x光检查时也忽略了人体上的服装和珠宝,为我们提供了最准确的疾病识别。这种经验运行、传输、技术和创建报告的精确度取决于您的经验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Employability of Deep Learning Tools and Techniques for an Early Detection and Diagnosis of Pulmonary Infection
Chest x-ray imaging is an essential screening and medication device for some lifethreatening infections; nonetheless, the screening instrument can't treat all patients due to the lack of radiologists. In this research, we are identifying 14 different types of chest infections from chest x-ray images. The task's key objective is to know the level of infection recognition of every 14 tests performed on the human chest with the most superior accuracy. Deep learning-based, typically medical picture classifiers, is one expected response. It likewise ignores the attire and jewels present on the human body while going through the x-ray test, giving us the most powerful accuracy of disease recognition. This experience runs, transfers, techniques, and creates reports with precision at some random reason of your experience.
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