Code for Healthcare 1st Place

PulsePal - EquiHER | Albania

Women are 50% more likely to be misdiagnosed after a heart attack (British Heart Foundation, 2016), wait on average four years longer to be diagnosed with autoimmune diseases (Angum, 2020), and 30% wait over a year for a brain tumour diagnosis, twice as long as men. These statistics reveal a major diagnostic bias in healthcare. EquiHER addresses this inequity through an AI-powered diagnostic risk assessment tool aligned with UN SDG 3.8: Universal Health Coverage. Using a neural network trained on synthetic medical data, it analyzes 15 clinical variables to identify patients, especially women, at higher risk of misdiagnosis, achieving an accuracy rate of 84–87%. By detecting gender-based symptom patterns often overlooked in clinical practice, EquiHER provides physicians with actionable, data-driven insights that support fairer medical decisions. This innovation enhances diagnostic accuracy, and empowers women to receive timely, accurate treatment, advancing both SDG 3 (Good Health) and SDG 5 (Gender Equality).