| مستخلص: |
The rapid evolution of AI models in preeclampsia prediction necessitates a comprehensive understanding of the multidimensional factors at play, including data integration, clinical relevance, ethical implications, and regulatory adherence. The integration of AI technology holds the promise of enhancing the accuracy of preeclampsia risk assessment, enabling timely interventions, and ultimately improving maternal and fetal well-being. Through the amalgamation of diverse data sources, ranging from electronic health records and physiological parameters to genetic insights and imaging data, AI models can provide personalized risk assessments that empower healthcare professionals to make informed decisions and tailor care strategies. While AI's potential is substantial, it's crucial to address challenges such as model complexity, ethical considerations, bias mitigation, clinical integration, and regulatory compliance. Collaborative efforts between AI developers, healthcare practitioners, ethicists, and regulatory bodies are pivotal to ensure responsible AI deployment and to maximize the benefits of AI technology in the context of preeclampsia prediction. [ABSTRACT FROM AUTHOR] |