التفاصيل البيبلوغرافية
| العنوان: |
Study of the Relationship between ICU Patient Recovery and TCM Treatment in Acute Phase: A Retrospective Study Based on Python Data Mining Technology. |
| المؤلفون: |
Wu, Zhiqun1 (AUTHOR), Wang, Xue2 (AUTHOR), Pan, Renlong1 (AUTHOR), Huang, Xiufu1 (AUTHOR), Li, Yuhan1 (AUTHOR) |
| المصدر: |
Evidence-based Complementary & Alternative Medicine (eCAM). 3/2/2021, p1-6. 6p. 1 Black and White Photograph, 2 Diagrams, 3 Charts. |
| مصطلحات موضوعية: |
*INTENSIVE care units, *EXPERIMENTAL design, *CRITICALLY ill, *CONVALESCENCE, *NEUROSURGERY, *PATIENTS, *MEDICAL technology, *ARTIFICIAL intelligence, *COMPARATIVE studies, *DESCRIPTIVE statistics, *ACUTE diseases, *CHINESE medicine, *DATA mining, *MEDICAL research |
| مستخلص: |
Background. Data was mined with the help of an artificial intelligence system based on Python, data was collected, and a database was established using a Python crawler, and the relationship between the outcome of neurosurgery ICU patients and treatment using traditional Chinese medicine was ascertained through data management and statistical processing. Method. The source data cases (n = 2237) were selected. By following the experimental design, data (n = 739) were obtained through artificial intelligence processing, including n = 480 in the group with traditional Chinese medicine treatment and n = 259 in the group without traditional Chinese medicine treatment. An evaluation was carried out using characteristics of patents' ICU stays and summated rating scales. Results. There were statistical differences in 5 evaluation items (P < 0.05), and other comparison items also showed data with results favoring the outcomes in the intervention group using traditional Chinese medicine. Discussion. Traditional Chinese medicine as an alternative medical protocol effectively alleviates the stress and treatment fatigue brought about by modern medicine. Artificial intelligence data mining is a favorable medium to quantify this. Python will play a greater role in future clinical research because of its own characteristics. [ABSTRACT FROM AUTHOR] |
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