RecruitingNCT06822413

Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis

A Novel Raman Spectroscopy-Based Method for Pan-Cancers Early Diagnosis Supported by Deep Learning: A Prospective, Single-Arm, Multicentre Study


Sponsor

Second Affiliated Hospital, School of Medicine, Zhejiang University

Enrollment

600 participants

Start Date

Sep 1, 2022

Study Type

OBSERVATIONAL

Conditions

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.


Eligibility

Plain Language Summary

Simplified for easier understanding

This study uses a technology called Raman spectroscopy combined with artificial intelligence (deep learning) to analyze blood or tissue samples and detect multiple cancers (including colorectal, gastric, liver, pancreatic, and esophageal cancers) at an early stage. **You may be eligible if...** - You have a confirmed diagnosis of one of the listed cancers (colorectal, gastric, liver, pancreatic, or esophageal) who has not yet received any treatment - OR you are a healthy person with no cancer or precancerous lesions - OR you have been diagnosed with precancerous lesions or non-malignant disease **You may NOT be eligible if...** - You have metastatic cancer or have two or more types of cancer simultaneously - You have already received cancer treatment (surgery, chemotherapy, radiation, or immunotherapy) Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Interventions

OTHERNo 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

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NCT06822413


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