This study investigates the use of Raman spectroscopy combined with deep learning to detect early-stage pan-cancer. The study focuses on analyzing blood samples to identify cancer-specific features using advanced technology.
The study evaluates whether the deep learning model can effectively classify patients based on their risk of cancer by analyzing Raman spectral data. It explores the accuracy and adaptability of different models and provides a clear understanding of how these models make diagnostic decisions.
- Who can participate: Individuals eligible for this study include those with a histopathological diagnosis of malignant tumors like colorectal and gastric cancer, as well as those in normal physiological conditions without tumors. Participants should not have undergone any cancer treatments. The study also includes patients with precancerous conditions.
- Study details: Participants will have their blood samples analyzed using Raman spectroscopy. The study involves using deep learning models to classify these samples.
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