The Role of Artificial Intelligence in Addressing Menopausal Mental Health Challenges
TL;DR
The potential of AI-driven tools-including machine learning algorithms, digital therapeutics, symptom trackers, and large language models-to improve the detection, monitoring, and personalized management of menopause-associated mental health disorders are discussed.
Abstract
Menopause marks a crucial transition in a woman’s life and is often accompanied by physical and psychological changes that can adversely affect mental health. Depression, anxiety, cognitive changes, and sleep disturbances are common during the menopausal transition, yet they are frequently underdiagnosed and undertreated, particularly in lowand middle-income countries. Emerging technologies, especially artificial intelligence (AI), offer new opportunities to narrow this care gap. Although AI has shown considerable promise in identifying menopause-related physical health conditions (e.g., osteoporosis and endometrial cancer), its use for mental health during this life stage remains limited. We discuss the potential of AI-driven tools-including machine learning algorithms, digital therapeutics, symptom trackers, and large language models-to improve the detection, monitoring, and personalized management of menopause-associated mental health disorders. By integrating genetic, clinical, lifestyle, and wearable data, AI systems may help predict risk, identify symptom patterns, and support tailored interventions. These approaches could enable scalable, accessible, and cost-effective mental healthcare, reduce stigma, and address service gaps. Harnessing AI in this area offers a significant opportunity to improve quality of life for millions of women worldwide.