管道(软件)
拉曼光谱
计算机科学
人工智能
唾液
机器学习
解码方法
模式识别(心理学)
医学
物理
算法
光学
内科学
程序设计语言
作者
Dario Bertazioli,Marco Piazza,Cristiano Carlomagno,Alice Gualerzi,Marzia Bedoni,Enza Messina
标识
DOI:10.1016/j.compbiomed.2024.108028
摘要
Raman Spectroscopy promises the ability to encode in spectral data the significant differences between biological samples belonging to patients affected by a disease and samples of healthy patients (controls). However, the decoding and interpretation of the Raman spectral fingerprint is still a difficult and time-consuming procedure even for domain experts. In this work, we test an end-to-end deep-learning diagnostic pipeline able to classify spectral data from saliva samples. The pipeline has been validated against the SARS-COV-2 Infection and for the screening of neurodegenerative diseases such as Parkinson's and Alzheimer's diseases. The proposed system can be used for the fast prototyping of promising non-invasive, cost and time-efficient diagnostic screening tests.
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