Generative AI and large language models (LLMs) have gained attention lately due to their impressive performance in various tasks such as text summarization and code generation. These models are now being utilized by companies, including those in the healthcare and life sciences industry, for purposes like medical information extraction and marketing content generation.
In this context, the focus is on using LLMs for designing marketing content aimed at creating awareness about diseases. Marketing content in the healthcare industry is crucial for disseminating information about health conditions and therapies among patients and healthcare providers. However, the content generation process can be slow and undergo numerous review cycles due to the sensitive nature of medical information and strict regulatory compliance.
To address this challenge, the AWS Generative AI Innovation Center developed an AI assistant for medical content generation. This system leverages LLM capabilities to generate curated medical content efficiently, reducing generation time significantly while providing more control to subject matter experts (SMEs) through an automated revision functionality. This revision process allows users to interact with the LLM, provide instructions, and give feedback for content refinement.
The system is designed to ensure accuracy, precision, and compliance with regulations through fact-checking and rules evaluation modules. These modules aim to assess the factuality of generated text and ensure alignment with specified rules and guidelines. By enhancing transparency and control over the generative logic of LLMs, the system offers a robust solution for medical content generation in disease awareness marketing.
The content creation process involves selecting medical references, providing guidelines, using an interactive UI to interact with the system, and leveraging services like Amazon Textract for data extraction. The processed data is then sent to the LLM through prompts for content generation, summarization, and revision. By integrating the generative pipeline with multiple services and functionalities, the system ensures seamless and efficient content creation tailored to the target audience’s needs.
Overall, the utilization of LLMs for medical content generation presents a promising opportunity to optimize processes, enhance operational efficiency, and empower SMEs and brand managers in the healthcare industry. The system’s revision feature enables iterative improvements to generated content, ensuring accuracy and compliance with regulatory standards. With a focus on scalability and robustness, the system demonstrates the potential of AI in driving transformative solutions for real-world applications.
Article Source
https://aws.amazon.com/blogs/machine-learning/medical-content-creation-in-the-age-of-generative-ai/
