RESUMEN
Data curation for a hospital-based cancer registry heavily relies on the labor-intensive manual abstraction process by cancer registrars to identify cancer-related information from free-text electronic health records. To streamline this process, a natural language processing system incorporating a hybrid of deep learning-based and rule-based approaches for identifying lung cancer registry-related concepts, along with a symbolic expert system that generates registry coding based on weighted rules, was developed. The system is integrated with the hospital information system at a medical center to provide cancer registrars with a patient journey visualization platform. The embedded system offers a comprehensive view of patient reports annotated with significant registry concepts to facilitate the manual coding process and elevate overall quality. Extensive evaluations, including comparisons with state-of-the-art methods, were conducted using a lung cancer dataset comprising 1428 patients from the medical center. The experimental results illustrate the effectiveness of the developed system, consistently achieving F1-scores of 0.85 and 1.00 across 30 coding items. Registrar feedback highlights the system's reliability as a tool for assisting and auditing the abstraction. By presenting key registry items along the timeline of a patient's reports with accurate code predictions, the system improves the quality of registrar outcomes and reduces the labor resources and time required for data abstraction. Our study highlights advancements in cancer registry coding practices, demonstrating that the proposed hybrid weighted neural-symbolic cancer registry system is reliable and efficient for assisting cancer registrars in the coding workflow and contributing to clinical outcomes.
RESUMEN
Heat stress has severe implications on the health of mice involving intestinal mucosal barrier damage and dysregulated mucosal immune response. This study was designed with long-term heat stress to detect the protective effect of terpinen4-ol on body weight, colon length, organ index, morphological structure, inflammatory cytokines expression, Claudin-2, Occludin, and TLR4 signaling pathway of colonic tissue in mice under heat stress. A study found that oral administration of terpinen4-ol helped against mortality and intestinal inflammation in a mouse model of acute colitis induced by heat stress (40 °C per day for 4 h) exposed for 14 consecutive days. The mice were divided into five groups including control, heat stress, terpinen4-ol low dose (TER LD: 5 mg/kg), medium dose (TER MD: 10 mg/kg), and high dose (TER HD: 20 mg/kg) group. Our study showed that the heat-stress terpinen4-ol group had improved body weight, colon length, and organ index, the number of white blood cells, lymphocytes, and neutrophils in the blood as compared to the heat stress group. In addition, results showed that heat stress upregulated the expression of TLR4, p65, TNF-α, and IL-10. While, in mice receiving the oral administration of terpinen4-ol, the production of TNF-α, IL-10, TLR4, and p65 was suppressed on day 1, 7, and 14 of heat stress. In addition Claudin-2, Occludin mRNA levels were upregulated in mice receiving terpinen4-ol on day 1, 7, and 14 of heat stress. Furthermore, the IL-6, IL-10, TNF-α serum levels were also upregulated in mice under heat stress, but in mice receiving the oral administration of terpinen4-ol, the IL-6, IL-10, TNF-α level was down-regulated on day 1, 7, and 14 of heat stress. Histomorphological examination found that as compared to the control group, the muscle layer thickness and villi height of mice in the heat stress group were significantly reduced, while the changes of the above indicators in the terpinene4-ol groups were improved than those in the heat stress group. In conclusion, the terpinen4-ol has a protective effect on colonic tissue damage induced by heat stress.