Medical coding errors aren’t just frustrating—they’re expensive, costing healthcare billions every year. But there might be some great developments to solve this soon! Yossi Shahak, CEO & Founder of Maverick Medical AI, is determined to deal with the challenges with the power of deep learning and synthetic data technology.
The healthcare sector is seeing a rapid surge in patient numbers, and more patients mean more complex medical documentation. As Shahak notes, this growth is dramatically amplifying the importance of accurate medical coding.
Errors aren’t just costly—they can directly affect patient care. Maverick’s solution: the innovative mCoder™, could turn out to be the first deep learning AI platform capable of autonomously analyzing complex, text-based patient records across all clinical sub-specialties.
Maverick Medical AI’s mCoder™ currently boasts an impressive 85% accuracy rate, though Shahak admits there’s plenty of room to improve. Their team is continually refining the technology, leveraging something intriguingly called “synthetic data.” Why synthetic? It turns out training deep-learning AI demands massive amounts of medical data—far more than is typically available. Maverick cleverly generates synthetic medical records to bolster training without compromising patient confidentiality.
Recently, Maverick Medical AI secured $5.5M in funding to accelerate development and expand the reach of their innovative platform. As a single-source solution, mCoder™ tackles coding across all clinical sub-specialties, empowering hospitals to streamline their coding processes and eliminate the chaos of juggling multiple solutions across departments.
Curious about the full vision behind Maverick Medical AI? Watch the insightful discussion with Yossi Shahak in this original video.
Now, we’d love to hear your thoughts! How soon do you think Maverick Medical AI will hit that magical 100% accuracy? Let us know in the comments below!
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