Deep Learning
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Claim Dashboard
Fraud, Waste and Abuse
Estimates that Fraud, Waste and Abuse in healthcare costs between $600 and $850 billion annually That’s nearly $9,000 per second - wasted in administrative system inefficiencies, and fraud and abuse alone.
Preventable Conditions and Avoidable Care | Lack of Care Coordination and Integration | Inefficiency and Errors | Unwarranted Use | Administrative System Innefficiency | Fraud and Abuse |
---|---|---|---|---|---|
$25 - 50B | $25 - 50B | $75 - 100B | $250 - 325B | $100 - 150B | $125 - 175B |
HǣlthTech Envisage provides insights into these core areas
Deep Learning
Conventional software has limitations - It solves problems by using fixed rules that require manual intervention - it can’t handle ambiguity or changes in meaning.
Our world is always changing and healthcare issues do not obey rigid rules or static software. Deep Learning derives knowledge by merging computational logic with an understanding of context. And, most uniquely, this technology learns, and grows smarter over time.
So what exactly is machine learning?
Machine Learning = Statistics + Data + Software. Machine learning (ML) falls under the umbrella of computer science. At its core, machine learning refers to the practice of training computers via software to recognize patterns and infer predictions, emulating a human-like ability to learn from “experience”. In ML, the “experience” that machines get is from humans not only inputting but also indicating useful data.
Our Solutions are different
Deep Learning derives knowledge by merging computational logic with an understanding of context. And, most uniquely, our technology learns, and grows smarter over time.
We believe technology is a means to an end.
We discovered that some ends require new kinds of technology and thinking
We use most advanced deep learning models to ensure every claim transaction tells a story.
Deep Learning is inspired by theories of how the brain recognizes patterns. The startling gains in fields as diverse as computer vision, speech recognition and the identification of promising new initiatives in healthcare
Conventional software has limitations - It solves problems by using fixed rules that require manual intervention - it can’t handle ambiguity or changes in meaning . Our world is always changing and healthcare issues do not obey rigid rules or static software. Deep Learning derives knowledge by merging computational logic with an understanding of context. And, most uniquely, this technology learns, and grows smarter over time.
Machine Learning = Statistics + Data + Software. Machine learning (ML) falls under the umbrella of computer science. At its core, machine learning refers to the practice of training computers via software to recognize patterns and infer predictions, emulating a human-like ability to learn from “experience”. In ML, the “experience” that machines get is from humans not only inputting but also indicating useful data.
Our Solutions are different
Deep Learning derives knowledge by merging computational logic with an understanding of context. And, most uniquely, our technology learns, and grows smarter over time.
We believe technology is a means to an end.
We discovered that some ends require new kinds of technology and thinking.
We use most advanced deep learning models to ensure every claim transaction tells a story.