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LLAMA 3.1 8B, 70B, 405B and LLAMA 3.2 3B
Sofya
30%
less time spent on paperwork during patient visits90%
customer satisfaction (CSAT) score+Feedback
Healthcare providers report better workflow efficiency and patient care outcomes1M
projected AI-assisted patient visits a month by 2025*All results are self-reported and not identifiably repeatable. Generally expected individual results will differ.
CASE STUDY
Healthcare solution brings Llama-powered clinical reasoning to patient care and record management
At a glance
Industry
HealthcareUse case
Streamlining patient assessments and automating documentation with AI-powered clinical reasoningGoal
Reduce administrative tasks and improve patient careLlama versions
Llama 3.1 8B, 70B and 405B; Llama 3.2 3BDeployment
Dedicated infrastructure on Oracle CloudTHEIR STORY
Reimagining healthcare with clinical reasoning AI
Sofya works with cutting-edge healthcare institutions and researchers to push the boundaries of healthcare innovation and bioinformatics. Built on a solid research foundation, Sofya continues to publish academic papers and open source its models and datasets as it commercializes its clinical reasoning technologies.
THEIR GOAL
Help healthcare providers focus on patients instead of paperwork
Digital healthcare administration is overwhelming providers. Physicians spend 2.5 to 8.4 hours documenting care in electronic health record platforms for every eight hours of scheduled patient time. Across specialties, the average is 3.4 hours.Sofya saw an opportunity to give time back to providers by streamlining healthcare record management and providing AI-powered assistants that could enhance clinical reasoning during patient consultations.
THEIR SOLUTION
Use Llama models to rationalize healthcare documentation, improve bedside care
Sofya developers fine-tuned a series of Llama models to create a multi-agent solution that helps structure healthcare data, applies clinical reasoning and assists providers during patient consultations. The Sofya clinical assistant guides providers through taking patient histories, flags concerns, offers diagnoses and creates personalized care plans.The team chose Llama models for their adaptability and capacity to produce high-quality clinical documentation. Open-source Llama freed Sofya developers to customize models and deploy them on their own infrastructure for maximum data control and security, a key requirement for the healthcare industry.
The Sofya clinical assistant helps capture patient information, formulate diagnoses and deliver care.
THEIR APPROACH
Fine-tune expert models for each role and application
Developers generated high-quality synthetic training data for the Sofya solution using Llama 3.1 405B and a combination of knowledge distillation and self-reflection prompts. To deliver clinical assistance from desktop to mobile, the solution uses trained and fine-tuned Llama 3.1 70B and 8B and Llama 3.2 3B models to balance latency, performance and computing resources.Llama models power the heart of the Sofya solution — a clinical reasoning system with humans in the loop that clarifies terms and structures healthcare information into unified, medical protocols and decision-support standards. These standards serve as programmatic rules that human caregivers, automated workflows and other applications can follow.
Fine-tuned Llama models power Sofya’s clinical reasoning system.
THEIR SUCCESS
Time savings for providers, lower costs for organizations
Sofya customers report providers are spending less time on documentation and that overall costs have decreased. Healthcare providers report better, more efficient workflows and, most importantly, improved patient care.
- 30% faster throughput in tokens per second vs. the previous model
- 90% customer satisfaction (CSAT) score
- 33% Healthcare providers report better workflow efficiency and patient care outcomes
- 1 million projected AI-assisted patient visits a month by 2025
“Llama stands out for being an open-source model, with an active community of developers and scientists who continuously collaborate, experiment and enhance the model. We always prioritize open-source solutions and are developing models and datasets that will be available to the community.”
Bruno Dorneles, Data Scientist, Sofya
“Llama is helping us hit our key goals: continuously improving AI accuracy and efficiency, scaling to one million consultations per month, expanding our product suite and growing our customer base.”
Marcelo Mearim, Brazil CEO, Sofya
“Llama automates data structuring, named entity recognition and question answering, improving efficiency, reducing errors and enabling healthcare professionals to focus on patient care.”
Bruno Dorneles, Data Scientist, Sofya
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