| dc.description.abstract | Technological advancements have the
potential to revolutionize prenatal care, improving
outcomes for expectant mothers and their unborn
children. This comprehensive review explores the
efficacy, challenges, and potential benefits of integrating
User Experience/User Interface (UX/UI), Natural
Language Processing (NLP), Machine Learning (ML),
and Data Mining in pregnancy care. The UX/UI aspect
focuses on user-centered design, providing intuitive
interfaces that cater to the unique needs of expectant
mothers. NLP techniques enable the early detection of
pregnancy abnormalities, allowing for timely
interventions and personalized care. ML algorithms aid
in predicting outcomes and identifying potential issues,
empowering healthcare providers to make informed
decisions. Data mining uncovers hidden patterns within
large datasets, facilitating early intervention strategies
and improved prenatal care. Future directions involve
refining UX/UI design, incorporating domain expertise in
NLP models, exploring advanced ML algorithms, and
expanding data mining analysis to include diverse
influencing factors. Integrating expert knowledge,
personalized approaches, ethical considerations, and
clinical validation is crucial. Multidisciplinary
collaborations will drive the development and
implementation of technology-driven solutions. The
paper concludes by discussing the potential benefits of
integrating technology into routine prenatal care
practices, including improved access to care, enhanced
patient engagement, and better health outcomes.
However, it also acknowledges the challenges and
limitations that need to be addressed for wider adoption
of technology-driven approaches. | en_US |
