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The goal of CloudMedx is to combine the latest machine learning, natural language processing and a clinical ontology to provide real time insights at the point of care. All data - clinical and non clinical, structured and unstructured - may be taken into account with the goal to improve outcomes
Clinical Analyzer
for optimal care delivery
The Clinical Analyzer analyzes patient's record to provide clinicians, nurses, and front line staff with insights to improve patient experience.  

For example, when a provider types a diagnosis such as “hypertension” or “HTN”,  the CloudMedx Clinical Analyzer detects the data and immediately puts it to use by:

a. Recording the ICD-10 code for it
b. Generating the risk using evidence based algorithms that use hypertension as a component
c. Returning a probability for the patient having other associated diseases (such as obesity and diabetes)  

Clinicians have the potential to save time by viewing all relevant patient information from past notes, intelligent point of care alerts  and course of action - based on big data, machine learning and evidence based medicine, thereby enabling clinicians to do what they went into medicine to do – focus on their patients.
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Key Features
Gaps in care
Real-time Collaboration
Real-time Risk Assessment
Automated Care Plans
Intelligent Clinical Alerts