Practitioners understand the importance of applied science, experience and intuitive insight in diagnosing patients. The practice of these three principles in medicine is a delicate weaving of information that is constantly in motion, and when pieced together in time, can help save patients’ lives. Medial EarlySign developed a unique, algorithm-powered toolset to help healthcare organizations and practitioners offer predictive care and predict the likelihood of diseases using EHR data to deliver high accuracy, and better treatment efficiency in everyday medical care.
The exponentially growing amount of Big Data that resides in medical systems may appear mute, yet a closer look reveals that hidden among the billions of data files are abnormal and subtle patterns unfolding with time, with the capacity to eventually become a life-altering prognoses. The story of modern medicine as we know it is changing thanks to new algorithmic capabilities that significantly enhance our access to machine-learning technology, and expand our clinical perspective to redefine the way the roles and capabilities of various stakeholders to leverage data and to deliver better outcomes and life-saving, personalized treatments.
Powered by machine learning algorithms that analyze and break down the mathematical composition of data, Medial EarlySign’s patented technology constructs connections between ordinary data and hidden insights – those untold stories in EHR files. These connections may help physicians identify health risks in patients that could lead to improvement in the healthcare system as well as personalized, timely medical treatment – a shift that can ultimately enrich the physician-patient relationship, and the way medicine is practiced today.