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Showing 3 open source projects for "improve"
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Experience simplified facility, payer, and contract management with our cutting-edge healthcare credentialing software. Designed to optimize the credentialing process, Credentialingspectrum enhances efficiency and effectiveness. Our one-click comprehensive automation sets the standard for provider credentialing software in the USA, offering unmatched convenience and excellence.
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Communication among care team members involves a complex relationship between people, devices, and hospital systems. You might be struggling with an overwhelming surge of data, gaps in your communication, or inefficient communication workflows. These challenges make your job harder and negatively impact patient outcomes. There’s a solution to help – Spok Care Connect®. Spok Care Connect is the unified communication platform that provides care team collaboration, closed loop communication, and secure messaging to enhance your clinical workflows. It’s possible for one unified communication platform to solve the multiple challenges across different areas, departments, and locations in your health system.
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Label Studio
Label Studio is a multi-type data labeling and annotation tool
... be used to prepare raw data or improve existing training data to get more accurate ML models. The frontend part of Label Studio app lies in the frontend/ folder and written in React JSX. Multi-user labeling sign up and login, when you create an annotation it's tied to your account. Configurable label formats let you customize the visual interface to meet your specific labeling needs. Support for multiple data types including images, audio, text, HTML, time-series, and video. -
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Diffgram
Training data (data labeling, annotation, workflow) for all data types
From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This includes... -
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Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you...
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