Early Screening and Subtype Identification of High-Risk Lung Nodules via Breathprint by Graphene eNose Platform: A Large Cohort Study

Early Screening and Subtype Identification of High-Risk Lung Nodules via Breathprint by Graphene eNose Platform: A Large Cohort Study

Early screening of individuals with high-risk lung nodules can significantly improve the prognosis of lung cancer patients, and accurate identification of lung nodule subtypes can provide guidance for medical treatment. Exhaled breath (EB) analysis via eNoses offers a quick and noninvasive approach,...

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Main Author: Xingyu Zhu (1372587) (author)
Other Authors: Qiaofen Chen (413800) (author), Jiajing Sun (8711571) (author), Lichen Zhang (5431988) (author), Zhengwei Huang (4855729) (author), Jingwei Xu (337549) (author), Haichuan Hu (109331) (author), Yuqi He (298660) (author), Zhao Chen (92571) (author), Xiaogang Ye (6904340) (author), Xueyin Chen (19690633) (author), Aotian Guo (18801535) (author), Sheng Lu (309194) (author), Tao Shen (209797) (author), Jianmin Wu (19537) (author), Zhengfu He (8653965) (author)
Published: 2025
Subjects:
Medicine
Cell Biology
Genetics
Physiology
Biotechnology
Developmental Biology
Cancer
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
reactive resistance response
including various benign
external test set
lung cancer patients
dimensionality reduction analysis
breath sampling accessory
427 healthy subjects
graphene enose platform
enose platform integrated
risk lung nodules
lung nodule subtypes
large population studies
89 – 0
enose platform
lung nodules
malignant subtypes
exhaled breath
breathprint analysis
2586 subjects
subtype identification
study demonstrates
solid validation
significantly improve
robust performance
rapid method
quality control
provide guidance
model achieved
metal ion
medical treatment
early screening
baseline data
accurate identification
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