About Dataset

This dataset was generated to simulate real-world clinical data for photonics-based smart surgical navigation systems, specifically within the domain of minimally invasive Hepatocellular Carcinoma (HCC) liver cancer surgery. It integrates optical (TEF, LDF), physiological, and biochemical signals to enable real-time differentiation between cancerous and non-cancerous liver tissues during surgery.

Comprising 3243 unique patient records, the dataset captures multimodal photonic signatures via a custom fiber-optic probe, alongside key clinical biomarkers such as AFP, bilirubin, and albumin levels. The dataset is structured to support the training and evaluation of machine learning and deep learning models for high-accuracy binary tissue classification during intraoperative navigation. It is particularly suitable for applications in AI-enhanced surgical precision systems.