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1.
J Healthc Eng ; 2021: 2087876, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34603642

RESUMO

In order to explore the quality management efficiency of applying big data and artificial intelligence in nursing quality index, a method of building a nursing management platform integrating nursing indicators and nursing events is proposed. Based on the investigation of the application demand of nursing information system, the method achieves timely data sharing and transmission through WLAN technology and realizes nursing management monitoring, nursing quality index enquiry, and automatic statistical analysis under the vertical management mode of nursing. The results showed that 77 people (73%) thought the time decreased, 19 people (18%) thought the time was the same, and 9 people (7%) thought the time increased. In terms of intelligent application and big data of nursing information management system, there is a significant difference in nursing management efficiency before and after using nursing management information system (P < 0.001). The nursing management control platform is designed and applied, and the nursing quality control method and actual management process are improved, which is very good for strengthening nursing quality management. The overall optimization of the quality control process is realized, which helps to mobilize the initiative and enthusiasm of nursing staff and continuously improve the effectiveness of nursing management and nursing efficiency.


Assuntos
Inteligência Artificial , Big Data , Humanos , Indicadores de Qualidade em Assistência à Saúde , Tecnologia
2.
Front Mol Biosci ; 8: 736272, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34917649

RESUMO

Background: Growing evidence has confirmed that populations with type 2 diabetes mellitus (T2DM) have an increasing risk of developing colorectal cancer (CRC). Thus, convenient and effective screening strategies for CRC should be developed for the T2DM population to increase the detection rate of CRC. Methods: Twenty serum samples extracted from five healthy participants, five T2DM patients, five CRC patients and five T2DM patients with CRC (T2DM + CRC) were submitted to data-independent acquisition mass spectrometry (DIA-MS) analysis to discover unique differentially altered proteins (DAPs) for CRC in patients with T2DM. Then, the diagnostic value of pregnancy zone protein (PZP) was validated by ELISA analysis in the validated cohort. Results: Based on DIA-MS analysis, we found eight unique proteins specific to T2DM patients with CRC. Among these proteins, four proteins showed different expression between the T2DM + CRC and T2DM groups, and PZP exhibited the largest difference. Next, the diagnostic value of serum PZP was validated by ELISA analysis with an AUC of 0.713. Moreover, the combination of PZP, CA199 and CEA exhibited encouraging diagnostic value, and the AUC reached 0.916. Conclusion: Overall, our current research implied that PZP could be regarded as a newfound serum biomarker for CRC medical diagnosis in T2DM patients.

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