Data Scientists
The ClosedLoop.ai platform is purpose-built to make healthcare-focused data scientists more effective at their jobs. By providing off-the-shelf models for many common healthcare use cases and automating many of the manual processes involved in traditional data science tasks, ClosedLoop allows data scientists to focus on the impactful problems that drive real value for organizations.
Learn MoreData scientists spend 80% of their time doing what they least like to do: collecting existing datasets and organizing data. That leaves less than 20 percent of their time for creative tasks like mining data for patterns that lead to new research discoveries.NIH Strategic Plan for Data Science
What We Do
ClosedLoop’s data science platform combines leading-edge AI tools and automation capabilities with healthcare specific content and expertise - enabling healthcare data scientists to build accurate and explainable predictive models with speed and ease.
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EASILY HANDLE MESSY HEALTHCARE DATA
Healthcare data is notoriously “messy.” ClosedLoop makes it simple to import raw healthcare data sets, such as medical claims, prescriptions, EMR, and custom data, without the need for tedious data normalization and cleansing.
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AUTOMATE FEATURE ENGINEERING
ClosedLoop helps healthcare data scientists build models and features smarter and faster—freeing them to focus their time on discovery of new insights.
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INCREASE ACCURACY
ClosedLoop provides data scientists with the tools they need to build highly accurate models and to continuously improve those models as new data and insights are surfaced.
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ENHANCE EXPLAINABILITY
ClosedLoop unpacks the “Black Box” of artificial intelligence allowing data scientists and clinicians to understand why and how factors impact a model’s prediction, driving faster adoption and better clinical results.
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SUPPORT COLLABORATION
ClosedLoop allows data scientists and clinicians to create and iterate on predictive models together.
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ENABLE SEAMLESS MODEL DEPLOYMENT
With ClosedLoop’s end-to-end solutions, it is easy to operationalize a model and automatically update predictions as new data arrives.
Today, we had our “kick-off” meeting and went over the details of all of the data we have available (labs, surveys, claims, clinical notes, SDoH, etc.). Shortly after the meeting we started building data adapters - the first step in the CL “process”. It was FREAKING AMAZING how well everything worked! As I started building those adapters, I saw the 100’s of features start to literally build themselves. Within a few hours, I was able to construct a data frame with all of the features that I’ll need to build a REALLY SOPHISTICATED readmissions model. Without the ClosedLoop platform, this would have LITERALLY TAKEN ME WEEKS to get to that point. Instead, tomorrow morning, I get to go in and start building really cool models. I can’t stress enough how FREAKING AMAZING this product is!- Data Scientist
Did You Know...
of a data scientists time is spent on tedious tasks they least like
increase in demand for data scientists since 2013
Growing demand has led to a nationwide shortage of 151,717 people with data science skills
Off-the-Shelf Models
Readmissions
There were approximately 3.3 million adult 30-day all-cause hospital readmissions in the U.S. in 2011, and they were associated with about $41.3 billion in hospital costs.
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Hospital Acquired Conditions & Infections
Annually, approximately 2 million patients suffer with HAIs in the U.S., and nearly 90,000 are estimated to die. The overall direct cost hospitals incur due to HAIs is estimated to be as high as $45 billion annually.
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Potentially Preventable Hospitalizations
Nearly 4.4 million hospital admissions for acute illness or worsening chronic conditions totaled $30.8 billion in hospital costs. Identify which admissions can be prevented.
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Chronic Disease—Onset or Progression
Heart disease, cancer, and diabetes are the leading causes of death and disability in the U.S. and they make up 90% of the nation's $3.3 trillion annual healthcare costs.
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