Title :
Development and validation of an AI-enabled mHealth technology for in-home pregnancy management
Author :
Kazantsev, Alexander ; Ponomareva, Julia ; Kazantsev, Pavel
Author_Institution :
Lab. of New Methods in Biol., Inst. for Biol. Instrum., Pushchino, Russia
Abstract :
The solution of perinatal morbidity and mortality problem lies in the development of an information technology for large-scale eHealth-enabled management of pregnancy, making use of personal mobile web monitors, cloud computing and artificial intelligence. The solution leads to halving the indices of perinatal morbidity and mortality, as well as the costs of pregnancy care at the same time. Lowering the costs of care in turn ensures the investment attractiveness of the eHealthcare services, and makes them affordable to low budget care providers. The advances of the technology are substantiated by the results already obtained. The concept of large-scale eHealth pregnancy management, making use of mobile/ wearable personal monitors, artificial intelligence and cloud computing is first proposed.
Keywords :
artificial intelligence; cloud computing; health care; medical information systems; obstetrics; artificial intelligence-enabled mHealth technology; cloud computing; in-home pregnancy management; information technology; large-scale eHealth pregnancy management; perinatal morbidity problem; perinatal mortality problem; personal mobile Web monitors; wearable personal monitors; Artificial intelligence; Biomedical monitoring; Cloud computing; Doppler effect; Fetal heart rate; Monitoring; Pregnancy; artificial intelligence; cloud computing; fetal monitoring; health care; mobile monitor; obstetrics;
Conference_Titel :
Information Science, Electronics and Electrical Engineering (ISEEE), 2014 International Conference on
Conference_Location :
Sapporo
Print_ISBN :
978-1-4799-3196-5
DOI :
10.1109/InfoSEEE.2014.6947804