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MDaudit uses AI to improve revenue outcomes for healthcare customers

AWS Machine Learning

MDaudit provides a cloud-based billing compliance and revenue integrity software as a service (SaaS) platform to more than 70,000 healthcare providers and 1,500 healthcare facilities, ensuring healthcare customers maintain regulatory compliance and retain revenue. says Nisheet Goenka, VP of Engineering at MDaudit.

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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. Regulations in the healthcare industry call for especially rigorous data governance.

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Foundational vision models and visual prompt engineering for autonomous driving applications

AWS Machine Learning

Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention.

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Monitoring AI solutions in healthcare

Nuance

The post Monitoring AI solutions in healthcare appeared first on What’s next.

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The Hidden Obstacles to Effective Planning. It’s Not What You Think!

Beyond Philosophy

A healthcare organization supplier that installs healthcare systems, meaning the back-end systems medical facilities use, called us to help with an installation that was going poorly. This perception massively affected what the healthcare organization saw them as. Regarding the healthcare supplier, that’s what we saw.

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Helping Press Ganey Accelerate Healthcare Outcomes

ConvergeOne

C1 helped Press Ganey drive transformational change with a new digital analytics and reporting platform, cloud infrastructure, and a team of 130 engineers to manage it. This platform would help providers improve safety, clinical excellence, workforce engagement, and the patient experience.

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Exploring summarization options for Healthcare with Amazon SageMaker

AWS Machine Learning

In today’s rapidly evolving healthcare landscape, doctors are faced with vast amounts of clinical data from various sources, such as caregiver notes, electronic health records, and imaging reports. In a healthcare setting, this would mean giving the model some data including phrases and terminology pertaining specifically to patient care.