Machine learning model helps identify patients at risk of postpartum depression

Posted by Michael Jannicelli | May 20, 2025 | Uncategorized | 0 |

Postpartum depression (PPD) affects up to 15 percent of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Researchers developed a machine learning model that can evaluate patients’ PPD risk using readily accessible clinical and demographic factors. Findings demonstrate the model’s promising predictive capabilities.

About The Author

Michael Jannicelli

Michael Jannicelli - "A PROVEN BUSINESS FIRESTARTER & BRANDING GENIUS" a true natural born Trendsetter. • Created over 100 products under 3 brands, sold in 30+ countries worldwide and influencing youth across the globe. • Featured in Forbes magazine +over 100 print publications, television talk shows, major motion pictures and national radio stations. • Co-founder and VP of Bliss beverage USA and President/co-founder of Socko International - fastest growing privately held beverage company in US (Forbes) with Hogan Energy & Raw Energy WWE. • Co-founder of Throwdown Industries (2003) - leading brand in multibillion dollar Impact/Action Sports Market (products designed for superior MN • Diagnosed with auto-immune diseases aged 13; using his experience to help others and promote a positive message while developing edgy products to benefit people with chronic illness.