Differences of lipid metabolism in patients with rectal cancer based on LIS

Yong Feng; Xiuli Qiao

doi:10.1117/12.2659314

30 November 2022 Differences of lipid metabolism in patients with rectal cancer based on LIS

Yong Feng, Xiuli Qiao

Proceedings Volume 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022); 124561Y (2022) https://doi.org/10.1117/12.2659314
Event: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 2022, Qingdao, China

Abstract

Rectal cancer is the most common malignant tumor of the digestive tract, and its incidence ranks third among all types of tumors. To investigate the differences in lipid metabolism between patients with rectal malignancies and healthy individuals, this study used the LIS information system to obtain a large amount of blood test data and used statistical software to perform correlation analysis. The data of the experimental group in this study came from the detection information of 502 patients with rectal cancer extracted by LIS. The data of the control group were obtained from the detection information of 1251 physical examiners. Human lipid metabolism is mainly expressed by indicators such as high-density lipoprotein, triglyceride, total cholesterol, low-density lipoprotein, apolipoprotein AI and apolipoprotein B. This study found that the blood lipid index of healthy people was significantly higher than that of patients with rectal cancer. This study uses the medical information data extracted by LIS as the experimental object. Through comparative analysis, when the human body develops rectal cancer lesions, the lipid metabolism level of the body will decrease significantly. The evaluation of blood lipid metabolism can provide a theoretical reference for improving the quality of life and prognosis of patients with rectal cancer.

Citation Download Citation

Yong Feng and Xiuli Qiao "Differences of lipid metabolism in patients with rectal cancer based on LIS", Proc. SPIE 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 124561Y (30 November 2022); https://doi.org/10.1117/12.2659314

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