Infertility affects millions of couples worldwide, often leading to significant emotional distress. Despite advancements in medical treatments such as IVF, the psychological challenges associated with infertility remain under-addressed. This study introduces a multi-modal AI system that integrates natural language processing (NLP), sentiment analysis, and voice interaction to provide personalized psychological support for individuals and couples experiencing infertility. A Randomized Controlled Trial (RCT) was conducted with 200 participants, comparing the AI intervention group to a control group receiving standard care. The AI system demonstrated significant reductions in anxiety and depression levels (GAD-7 and PHQ-9), as well as improvements in emotional well-being (PANAS). The intervention group reported higher user satisfaction (85%) and engagement, with participants using the system an average of four times per week. The AI system ability to offer empathetic, real time emotional support was highly rated by users. However, challenges such as cultural sensitivity and voice interaction accuracy were noted. This study highlights the potential of AI in mental health, particularly in addressing the often overlooked psychological needs of individuals facing infertility. The findings suggest that AI-driven solutions can bridge gaps in psychological care by providing scalable, cost-effective, and accessible support. Further research is needed to refine the system capabilities and explore its long-term impact on emotional well-being.
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