AI and Apps Aid Research into Endometriosis
Noémie Elhadad, PhD, an associate professor and chair of biomedical informatics at Columbia University’s Vagelos College of Physicians and Surgeons, is on a mission to uncover more information about endometriosis. Having been diagnosed with the condition at a young age of 13, Elhadad understands firsthand the lack of knowledge surrounding this chronic illness that impacts millions globally.
Her dedication led her to create the research mobile app, Phendo, which has attracted 17,000 users who share their experiences living with endometriosis. The primary aim of Phendo is to establish a comprehensive database of patients’ day-to-day symptoms, treatment methods, triggers, and overall disease progression.
Endometriosis manifests differently in individuals, often causing years of debilitating pain before a proper diagnosis is made. Symptoms can range from painful menstruation to gastrointestinal and genitourinary issues, along with chronic pain in various body areas. Through the data collected via Phendo, researchers are gaining insights into the inflammatory nature of endometriosis, shedding light on potential treatment avenues.
Elhadad acknowledges the complexity of managing endometriosis and the need for personalized strategies tailored to each patient. Leveraging AI technology like reinforcement learning, her team aims to develop tools that analyze patient responses to different interventions and recommend personalized self-management approaches focused on reducing pain and fatigue.
Furthermore, Elhadad is working on an AI-based screening tool that scans electronic health records for patterns indicative of endometriosis. Rather than replacing healthcare providers, this tool aims to assist in identifying potential cases early, prompting discussions between patients and specialists for timely intervention.
As the research into endometriosis continues to evolve, the work of experts like Noémie Elhadad highlights the importance of leveraging AI and mobile applications to gather valuable data, enhance patient care, and ultimately improve outcomes for those affected by this complex condition.
