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Updated: Jun 18, 2026

Neuroimaging Field Methods Using Functional Near Infrared Spectroscopy (NIRS) Neuroimaging to Study Global Child Development: Rural Sub-Saharan Africa
08:10

Neuroimaging Field Methods Using Functional Near Infrared Spectroscopy (NIRS) Neuroimaging to Study Global Child Development: Rural Sub-Saharan Africa

Published on: February 2, 2018

使用DE-SAMNet模型对多类肺癌分类进行Grad-CAM增强可解释的深度学习

Murat Kılıç1, Merve Bıyıklı1, Abdulkadir Yelman2

  • 1Turgut Ozal Medical Center, Department of Thoracic Surgery, Faculty of Medicine, Inonu University, Malatya 44280, Türkiye.

Diagnostics (Basel, Switzerland)
|March 14, 2026
PubMed
概括

这项研究介绍了DE-SAMNet,这是一种用于从CT扫描中准确分类肺癌的深度学习模型. 可解释的AI框架提高了诊断可靠性,并支持早期检测.

关键词:
这是分类分类的分类.密集的网络121有效的网络b0肺癌是一种肺癌.空间注意模块的空间注意模块

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Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study04:44

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Published on: July 21, 2021

Scanning Dos and Don'ts: Using Magnetic Resonance Imaging in Awake Children Aged 3 to 5 Years to Assess Brain Structure and Function07:31

Scanning Dos and Don'ts: Using Magnetic Resonance Imaging in Awake Children Aged 3 to 5 Years to Assess Brain Structure and Function

Published on: March 10, 2026

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