Objective To analyze the literatures about artificial intelligence in cancer research in Web of Science (WOS) core collection database in 2010-2019 and summarize research hot spots and development trends. Methods Through bibliometrics methods and CiteSpace information visualization software, we applied the visual analysis of relevant literature on artificial intelligence in the field of cancer research retrieved from the Web of Science core collection database from 2010 to 2019. Results The number of published articles about artificial intelligence in the field of cancer research had been increasing year by year. The United States ranked first in the number of published articles in this field, the number of citations and cooperation capabilities. Although the number of published articles in China ranked the second, the number of citations was low. The hot spots of artificial intelligence in cancer research were mainly breast cancer and lung cancer. Machine learning, neural network and other methods were used to build models, which were used in basic cancer research, clinical diagnosis, treatment and prognosis prediction. The research frontiers were the methodological research of artificial intelligence, the research on the occurrence and classification of cancer and the research of protein in this field. Conclusion It will effectively promote the development of artificial intelligence in cancer research in China by learning the hot spots and cutting-edge technologies of international research, focusing on international cooperation and cooperation among national institutions and strengthening cross-disciplinary research.

Objective: To understand the cognitive and management status of breast cancer patients with expectant nausea and vomiting in breast cancer patients, and to provide reference for taking targeted measures to improve the symptoms of nausea and vomiting. Methods: From March to May 2018, 10 breast surgical nurses were selected by the purpose sampling method. The phenomenological research methods in qualitative research were used to interview them. The Colaizzi data analysis principle was used to analyze the data and refine the theme. Results: A total of five themes were extracted: nurses generally knew the impact of nausea and vomiting on patients; lack of knowledge about the expected nausea and vomiting of chemotherapy; nausea and vomiting has not been evaluated as an independent symptom; there is still no targeted, systematic management Measures; lack of attention is a major obstacle to the management of nausea and vomiting in patients. Conclusion Nurses should strengthen the knowledge of chemotherapy-predicted nausea and vomiting in breast cancer patients, and effectively evaluate patients with nausea and vomiting. Nursing managers should formulate corresponding standardized interventions to improve patients' nausea and vomiting according to the existing problems. Improve the quality of life of patients.

Objective: To evaluate the effects of continued acceptance and commitment therapy intervention on post-traumatic growth of postoperative patients with breast cancer. Methods: According to the hospitalization time, 120 patients with breast cancer were divided into observation group (62 cases) and control group (58 cases). From January to December 2017, 58 patients were used as control group. Regular health education and discharge follow-up were performed. Intervention with the commitment therapy 3 times; 62 patients from January to December 2018 were selected as the observation group. On the basis of the control group, the patient continued to receive and commit the intervention for 3 to 4 times from February to March after discharge. The post-traumatic growth status of patients before, at the time of discharge (after the intervention), at the hospital for 2 months, at the hospital for 3 months, and at the hospital for 6 months was assessed using the Simplified Chinese version of the Post-Treatment Growth Rating Scale (PTGI). Results: There was no significant difference in the post-traumatic growth scores between the two groups (P>0.05). The post-traumatic growth scores of the two groups were 67.02±14.17, 66.93±14.24, which were better than 51.72±11.65, 51.86±11.67 before the intervention (t= 7.634, 7.725, P<0.05). At 3 months and 6 months after discharge, the post-traumatic growth scores of the observation group were (67.12±14.07) and (68.21±14.48), which were significantly better than the control group (54.17±11.64). 54.02±11.12), the difference was statistically significant (t= 7.957, 7.674, P<0.01). Conclusion Acceptance and commitment therapy intervention during hospitalization can effectively improve post-traumatic growth of postoperative patients with breast cancer. Continued admission and commitment therapy intervention after discharge can provide patients with out-of-hospital continuous care programs to improve post-traumatic growth of postoperative patients with breast cancer. It has a better long-term effect than the control group.