Big data analytics in disclosing IVF-ET patients'deeds based on artificial intelligence
Objective:To investigate the needs of the patients who were accepting or intended to accept in vitro fertilization-embryo transfer(IVF-ET)on social media based on artificial intelligence(AI)and big data analytics,which will provide a reference for medical staff.Methods:By collecting internet data and using algorithm modeling,we collected the information exchanged by IVF-ET patients on social media from 2010 to 2019.And we analyzed the distribution of patients'age and gender,trends in online communication regarding health information,types of diseases patients suffered from,the medication,patients'concerns and the factors related to patients'emotion.Results:During 2010-2019,IVF-ET patients had been increasingly sharing IVF-ET-related information on social media.The population of IVF-ET patients aged 30-35 was the largest on the Internet.Most of the patients who chose to consult IVF-ET-related information online were female infertile patients.In the case of medication,the most frequently mentioned drug was progesterone injection,the most frequently mentioned way of medication was vaginal administration,and the largest number of patients were treated with one kind of progesterone drugs.The main factors patients cared about were negative emotions,pregnancy indicators and economic factors.Patients who had failed in IVF-ET or received vaginal administration of progesterone were prone to have negative emotions.Conclusions:AI-based big data analytics can help specialists and nurses understand the actual needs of IVF-ET patients.Both clinicians and nurses need to strengthen education and instruct patients to establish correct understanding,as well as maintain a good emotional state.
In vitro fertilization and embryo transferArtificial intelligenceAssisted reproductive technologyNeedsEmotion
万方数据
维普
