Increase in asset
AI-driven clinical decision making
Eugenie’s AI-backed algorithms can scrutinize a huge volume of patient data to establish similarity with past events to detect any medical discrepancies. Machine Learning-based models can analyze data from other factors such as previous diagnosis, drug history, lifestyle, genetic profiles, etc. to generate alerts, which can help practitioners in decision making.
Ray-finn can analyze extensive data from various operational departments to generate comprehensive insights to understand gaps in demand and supply of resources. This can result in the smooth running of daily operations of hospitals by effective resource allocation in terms of labor, logistics, and medications.
Customized patient care
Eugenie’s AI workbench can process patient health data from various sources, which can generate personalized recommendations and alerts for each patient that can equip practitioners to act on time.