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Description
Aptarro's HCC Coding Engine is a cutting-edge AI solution that works in harmony with electronic medical records and practice management systems, enabling real-time scanning of every patient interaction to automatically identify and rectify coding discrepancies, ensuring that all Hierarchical Condition Category (HCC) diagnoses are correctly recorded for effective risk adjustment and revenue optimization. Utilizing established industry rules and advanced machine learning algorithms, the engine highlights high-priority encounters for coder assessment, significantly enhancing coder productivity by as much as 300% without increasing the workload for providers, while simultaneously minimizing denials through instant validation and compliance enhancements. The system features exception-based workflows, user-friendly dashboards that track RAF score trends, integrated audit trails, and logging capabilities, and offers rapid deployment within current processes, allowing organizations to experience immediate returns on investment during their initial billing cycle and recover millions in overlooked revenue, all while upholding clinical focus and ensuring the integrity of documentation. This innovative approach not only streamlines the coding process but also empowers healthcare organizations to maximize their financial performance without compromising patient care.
Description
StarCoder and StarCoderBase represent advanced Large Language Models specifically designed for code, developed using openly licensed data from GitHub, which encompasses over 80 programming languages, Git commits, GitHub issues, and Jupyter notebooks. In a manner akin to LLaMA, we constructed a model with approximately 15 billion parameters trained on a staggering 1 trillion tokens. Furthermore, we tailored the StarCoderBase model with 35 billion Python tokens, leading to the creation of what we now refer to as StarCoder.
Our evaluations indicated that StarCoderBase surpasses other existing open Code LLMs when tested against popular programming benchmarks and performs on par with or even exceeds proprietary models like code-cushman-001 from OpenAI, the original Codex model that fueled early iterations of GitHub Copilot. With an impressive context length exceeding 8,000 tokens, the StarCoder models possess the capability to handle more information than any other open LLM, thus paving the way for a variety of innovative applications. This versatility is highlighted by our ability to prompt the StarCoder models through a sequence of dialogues, effectively transforming them into dynamic technical assistants that can provide support in diverse programming tasks.
API Access
Has API
API Access
Has API
Integrations
ChatGPT
CodeQwen
Git
GitHub
LM Studio
OpenAI
Python
Tabby
Taylor AI
Visual Studio Code
Integrations
ChatGPT
CodeQwen
Git
GitHub
LM Studio
OpenAI
Python
Tabby
Taylor AI
Visual Studio Code
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Aptarro
Country
United States
Website
www.aptarro.com/hcc-coding
Vendor Details
Company Name
BigCode
Founded
2023
Website
huggingface.co/blog/starcoder