Objective To conduct an in-depth analysis and feature extraction of the transcriptomics data of 10 types of cancers in order to realize the staging diagnosis of cancer samples.Methods The transcriptomics data of the top 10 cancers having the highest incidence were amassed from the UCSC Xena website,which comprised 4 938 samples and 59 428 genes.With the aid of variational autoencoder,we developed an incremental feature ranking and selection variational autoencoder(IFRSVAE)based on feature importance ranking and incorporating the masking algorithm and the Incremental Feature Selection(IFS).Subsequently,the performance efficiency of our IFRSVAE model was evaluated in conjunction with Random Forest(RF),Support Vector Machine(SVM),and eXtreme Gradient Boosting(XGboost),and it was also compared with other methods.Results Our research extracted 21 features for the ensuing classification.In comparison to the conventional variational autoencoder,recursive feature elimination,and Lasso regression models,the IFRSVAE model attained more favorable performance across all 3 classifiers(highest AUC value,and well performed other indicators).Notably,the IFRSVAE-RF exhibited the most outstanding performance,with an AUC value reaching 85.49%(95%CI:83.24%～87.74%).Moreover,Shapley additive explanations(SHAP)interpretable model illustrated well contributions of the features in our model.Conclusion Our developed IFRSVAE shows certain effectiveness in feature extraction.The constructed IFRSVAE-RF model demonstrates relatively good performance in the task of cancer staging diagnosis,which providing a new and referable idea for research orientation of deep-learning-based diagnostic methods for cancer staging.

In recent years,public hesitancy to vaccinate has come to the fore and can hinder the advancement of immunization programs.It is important to increase public confidence in vaccines and to rationally and effectively promote the immunization behavior of the population.Based on behavioral economics theory,it combines the anchoring effect,loss aversion,two-systems theory,and the herd effect to explore the irrational factors and decision-making preferences behind the public's vaccination decisions,and then proposes discourse strategies for effective boosting to increase the public's confidence in vaccination.

In recent years,public hesitancy to vaccinate has come to the fore and can hinder the advancement of immunization programs.It is important to increase public confidence in vaccines and to rationally and effectively promote the immunization behavior of the population.Based on behavioral economics theory,it combines the anchoring effect,loss aversion,two-systems theory,and the herd effect to explore the irrational factors and decision-making preferences behind the public's vaccination decisions,and then proposes discourse strategies for effective boosting to increase the public's confidence in vaccination.

In recent years,public hesitancy to vaccinate has come to the fore and can hinder the advancement of immunization programs.It is important to increase public confidence in vaccines and to rationally and effectively promote the immunization behavior of the population.Based on behavioral economics theory,it combines the anchoring effect,loss aversion,two-systems theory,and the herd effect to explore the irrational factors and decision-making preferences behind the public's vaccination decisions,and then proposes discourse strategies for effective boosting to increase the public's confidence in vaccination.

In recent years,public hesitancy to vaccinate has come to the fore and can hinder the advancement of immunization programs.It is important to increase public confidence in vaccines and to rationally and effectively promote the immunization behavior of the population.Based on behavioral economics theory,it combines the anchoring effect,loss aversion,two-systems theory,and the herd effect to explore the irrational factors and decision-making preferences behind the public's vaccination decisions,and then proposes discourse strategies for effective boosting to increase the public's confidence in vaccination.

In recent years,public hesitancy to vaccinate has come to the fore and can hinder the advancement of immunization programs.It is important to increase public confidence in vaccines and to rationally and effectively promote the immunization behavior of the population.Based on behavioral economics theory,it combines the anchoring effect,loss aversion,two-systems theory,and the herd effect to explore the irrational factors and decision-making preferences behind the public's vaccination decisions,and then proposes discourse strategies for effective boosting to increase the public's confidence in vaccination.

In recent years,public hesitancy to vaccinate has come to the fore and can hinder the advancement of immunization programs.It is important to increase public confidence in vaccines and to rationally and effectively promote the immunization behavior of the population.Based on behavioral economics theory,it combines the anchoring effect,loss aversion,two-systems theory,and the herd effect to explore the irrational factors and decision-making preferences behind the public's vaccination decisions,and then proposes discourse strategies for effective boosting to increase the public's confidence in vaccination.

In recent years,public hesitancy to vaccinate has come to the fore and can hinder the advancement of immunization programs.It is important to increase public confidence in vaccines and to rationally and effectively promote the immunization behavior of the population.Based on behavioral economics theory,it combines the anchoring effect,loss aversion,two-systems theory,and the herd effect to explore the irrational factors and decision-making preferences behind the public's vaccination decisions,and then proposes discourse strategies for effective boosting to increase the public's confidence in vaccination.

Objective To construct a telemedicine-based home care system of palliative care for end-of-life cancer patients,and to evaluate its application effect.Methods The construction of the system was based on the literature research,interview results of the patients and their caregivers,and expert group meeting discussions.From May to August 2023,a total of 88 patients,who were about to be discharged from the palliative care ward of a cancer hospital in Hunan Province,were selected as the study subjects using a convenient sampling method,and then they were divided into an experimental group and a control group according to the order of admission.The experimental group was given home care services based on the system,while the control group was given routine discharge guidance and follow-up visits.The duration of the intervention was 8 weeks.The Chinese version of the Edmonton Symptom Assessment Scale and the Chinese version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 palliative were used to evaluate the symptom burden and quality of life between 2 groups before and after intervention;the Telemedicine Satisfaction Questionnaire was used to evaluate the care satisfaction of the experimental group.Results The system of patient side includes 8 main features,namely personal health record establishment,doctor-patient communication,palliative care knowledge library,medication assistance,smart reporting and monitoring,intelligent Q&A,intelligent follow-up,and intelligent forms.The healthcare professional side includes 7 main functions,namely workbench,case management,follow-up management,warning reminder,popularization push,statistical analysis and user management.A total of 67 patients completed the intervention,with 33 in the experimental group and 34 in the control group.The symptom burden of the experimental group was lower than that of the control group(P＜0.05);the quality of life in the experimental group was better than that in the control group(P＜0.05);the score of care satisfaction was(59.00±6.66),which indicated a high level of satisfaction.Conclusion The system can reduce the symptom burden and improve the quality of life of end-of-life cancer patients with good practicality

Objective To evaluate the effect of Internet-based psychosocial intervention for primary caregivers of patients with terminal stage cancer.Methods The relevant randomized controlled trials of Internet-based psychosocial intervention for primary caregivers of patients with terminal stage cancer were systematically searched from 10 databases,such as Chinese Biomedical Literature Database,CNKI,PubMed,Embase and CINAHL and etc.The search period was from the establishment to December 18,2023,and 2 investigators screened the literature according to inclusion and exclusion criteria and extracted data.Cochrane Manual 5.1.0 was used to assess the quality of the literature.Meta-analysis was performed using Revman 5.4 software.Results A total of 9 pieces of the literature including 592 primary caregivers were included.Meta-analysis showed that Internet-based psychosocial intervention reduced the level of anxiety and depression for primary caregivers of patients with terminal stage cancer[MD=-1.64,95％CI(-2.68,-0.59),P=0.002]and the burden of care[SMD=-0.39,95％CI(-0.60,-0.18),P＜0.001],and improved quality of life[SMD=0.25,95％CI(0.01,0.48),P=0.040];further research is needed to explore the effect of reducing the level of distress[MD=-0.88,95％CI(-1.91,0.16),P=0.100].Conclusion The Internet-based psychosocial intervention is effective in improving the anxiety,depression and the burden of care of the primary caregivers of patients with terminal stage cancer,and it can improve the quality of life;further research is needed to explore the level of distress reduction.