Elythea
Elythea is a machine learning tool specifically designed to identify expecting mothers who are at a high risk of pregnancy complications weeks in advance of delivery. It aims to improve maternal healthcare by addressing preventable pregnancy complications and reducing pregnancy-related deaths. Elythea focuses on various complications, including postpartum hemorrhage, preterm labor, preeclampsia, eclampsia, and failed vaginal birth after cesarean (VBAC).
The tool offers a three-step process. Firstly, it seamlessly integrates with your electronic health record (EHR) system, whether it is cloud-based or on-premises, minimizing administrative effort. Secondly, Elythea analyzes patient demographics, medical history, and existing clinical risk factors to promptly identify high-risk mothers throughout their pregnancy, starting from the first visit. Lastly, it provides evidence-based recommendations to healthcare providers, enabling early intervention and counseling to prevent expensive complications.
Elythea boasts a substantial amount of patient data, with over 300 million data points used in model training. The tool achieves prediction accuracy of up to 85% and an AUC ROC score of up to 0.85. It has been utilized in clinical studies conducted in multiple countries.
The team behind Elythea includes its founder and CEO, Reetam Ganguli, who has substantial experience in the medical field, and Rishik Lad, the co-founder and CTO, who previously worked as a machine learning engineer. The advisory team consists of medical professionals and machine learning experts.
Overall, Elythea aims to improve maternal outcomes, contain healthcare costs, and simplify the lives of healthcare providers by offering a partnership to health providers, employers, and plans.
