Implementing an AI pilot project for clinical documentation software requires meticulous planning and strategic execution. Here are the essential best practices for ensuring the success of your AI pilot project.

In the rapidly evolving field of artificial intelligence, NIST's new Generative Artificial Intelligence (genAI) Profile guidance offers crucial strategies for managing AI risks. This post breaks down the essential tasks under four categories: Govern, Map, Measure, and Manage.

Introduction The National Institute of Standards and Technology (NIST) has crafted a robust framework aimed at guiding the responsible development and deployment of generative artificial intelligence. The draft Generative AI Intelligence Profile addresses critical concerns that span safety, security, ethical standards, and compliance issues.

Introduction In the rapidly evolving landscape of healthcare, artificial intelligence (AI) is transforming the way clinical documentation is managed. As biotech and pharmaceutical companies, academic institutions, and healthcare systems increasingly adopt AI tools to improve the accuracy and efficiency of clinical information, the need for robust governance structures becomes imperative.

Toward the end of clinical document development, a quality control (QC) review is needed to verify data, check facts, ensure structure is internally logical and meets regulatory requirements, and proofread for typographical errors or inconsistencies.

In today’s digital age, accessibility in technology is not just a feature—it's a necessity. As a disabled-owned company, we recognize the importance of creating tools that everyone can use, particularly when it comes to AI-enabled and intelligent authoring systems.