Diagnostic errors in the healthcare industry can mean life or death for a patient. Gaps in collaboration, communication, IT systems, and overall information commonly contribute to ill-informed medical decisions. Healthcare professionals need to have access to many datasets at the time decisions are made so they can make more accurate diagnoses and treatment decisions and ultimately improve patient care.
The expanding volume of patient information puts the healthcare industry in a strong position to take advantage of artificial intelligence (AI) and machine learning (ML). Models can be created to ingest extensive amounts of raw data from all sources available, analyze it beyond human capability, and extract insights that aid physicians in making diagnostic decisions. Leveraging information from clinical trials, medical journals, and images helps physicians make more accurate and personalized health recommendations all while remaining compliant with HIPPA.
Implementing a fast, accurate, reproducible, and cost-effective medical diagnostic framework is the power needed to make accurate medical decisions and provide better patient care. See how Anaconda Enterprise can improve data science workflows in healthcare by booking a demo.