Gen AI Platform
Industry
Healthcare
Organization Type
Healthcare Organization
Tagline
Empowering Healthcare with AI: Personal Health Companion
Services
Solution Design, Prototype, Design, Development, Deployment
About the Client
The client is a healthcare organization that aims to enhance patient care through advanced AI solutions. They are particularly interested in leveraging Large Language Models (LLMs) to analyze and summarize extensive patient data, reports, and medical histories. This initiative is driven by the need to improve patient engagement, streamline documentation, and provide healthcare professionals with quick access to relevant information and insights.
The Problem
The healthcare organization faces the challenge of efficiently summarizing and analyzing vast amounts of patient data to support personalized treatment recommendations. This involves processing electronic health records, medical reports, and genomic data to identify patterns and correlations, leading to tailored treatment plans and improved patient outcomes. The organization requires a solution that can analyze patient data to support personalized treatment recommendations, enabling precision medicine and optimizing treatment strategies based on individual patient characteristics.
Our Approach
To address this challenge, we propose the development of a user interface that collects user data and provides a summary of previous and current tests. This system will utilize SQL agents to retrieve previous readings and create a summary based on these readings. Following this, an LLM model will be employed to generate a summary report based on certain parameters. This approach is designed to enhance patient care by providing timely information and support, thereby improving the patient care experience.
Our Development Process
The development process involves building a website with frontend and backend framework along with OpenAI API integration. This solution employs self-learning machine learning models to deliver precise responses to users' previous results. The Gen AI model-based can precisely respond to end-user queries and provide accurate summaries, thereby increasing end-user productivity. Fine-tuning the LLM for specific tasks, such as summarization, can further enhance the quality of the generated summaries. generating a summary with an LLM involves sending a request to the model with parameters such as the model to use, the system prompt (instructions), the user input (the text to be summarized), and the temperature (which controls the creativity of the output). The temperature parameter is particularly important for summarization tasks, as a higher temperature can lead to more creative but potentially less accurate summaries, while a lower temperature results in more predictable and consistent summaries
Tech Stacks Used
Open AI ChatGPT 4.0
Amazon EC2
Amazon S3
ReactJS
LangChain
Python
The Results
This solution is designed to revolutionize healthcare by leveraging the power of LLMs to analyze and summarize patient data, thereby enhancing patient care and outcomes.
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