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Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis
Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University
Summary
The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening. The study includes healthy individuals, patients at risk of cancer, and patients with diagnosed cancers. The main questions it aims to answer are: * Evaluating the deep-learning model's accuracy and specificity in identifying cancer-specific features in Raman spectral data and determining whether this method can accurately classify patients based on risk. * Identifying which model is more adaptable to the Raman spectrum * Providing an interpretable analysis of the model-generated diagnosis Participants are already being diagnosed and follow-up to determine the type of cancer.
Official title: A Novel Raman Spectroscopy-Based Method for Pan-Cancers Early Diagnosis Supported by Deep Learning: A Prospective, Single-Arm, Multicentre Study
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
600
Start Date
2022-09-01
Completion Date
2025-07-28
Last Updated
2025-04-24
Healthy Volunteers
Yes
Conditions
Interventions
No Interventions
All blood samples from participating patients were obtained from routine clinical blood tests conducted during hospital admission or other necessary medical evaluations, followed by serum extraction.
Locations (4)
The First Affiliated Hospital to Nanchang University
Nanchang, Jiangxi, China
The Second Affiliated Hospital to Nanchang University
Nanchang, Jiangxi, China
Huashan Hospital Affiliated to Fudan University
Shanghai, Shanghai Municipality, China
The Second Affiliated Hospital of Zhejiang University School of Medicine
Hangzhou, Zhejiang, China