AI to Automate Patient Insights
Artificial Intelligence (AI) To Automate Understanding What Matters Most to Patients
Our newest artificial intelligence (AI) powered features, further automate patient insight generation for customers. Building on years of work with OpenAI, THREAD has launched enhanced GPT-powered features within its inVibe voice data capture solution to accelerate data-generated insights that support research design, patient recruitment and retention.
Sponsors and CRO’s can interact directly with these AI tools in the platform to ask complex questions about their data and receive unique insight summaries by:
- Utilizing the “Smart Summary” feature to receive an immediate AI-powered response offering a draft write-up of data insights
- Engaging with the “Playground” feature to interact in real-time with the AI in exploring the dataset for patient insights
- Obtaining enhanced sentiment analysis solutions via new automations
THREAD’s Experience and Use Cases Leveraging AI
How GPT-3 Unlocks Deeper Listening at inVibe
THREAD’s inVibe solution has developed AI algorithms since joining OpenAI’s API Beta program in early 2021. This multi-year experience with GPT has provided a pathway of discovery for innovative concepts and has led to the new features available on the platform today.
Learn more about their process in developing these AI features →
Realizing The Potential Of AI And Machine Learning in Clinical Research
AI and machine learning has more potential to improve efficiencies in clinical research. The benefits of AI provides use cases in streamlining the research process, enhancing data analysis, and ultimately accelerating the development of effective treatments.
AI-Driven Automation: Understanding Its Power to Transform Clinical Research
THREAD announced its collaboration with Amazon Web Services (AWS) and their combined work to introduce AI-powered enterprise-scale automation into THREAD’s decentralized clinical trial (DCT) platform. AI-driven automation has the power to transform clinical research by streamlining data collection and analysis, reducing errors, and improving patient outcomes.
