LG AI Research Develops AI Model on AWS for Rapid Cancer Diagnosis
LG Group’s AI think tank uses AWS to identify cancer risks earlier
Amazon SageMaker helps LG AI Research reduce genetic testing time from two weeks to less than one minute to accelerate patient diagnosis
EXAONEPath achieves an average accuracy of
“AWS allows us to accelerate our AI research, bringing accessible and rapid cancer screening closer to reality,” said Hwayoung (Edward) Lee, vice president of LG AI Research. “By leveraging AWS, we can train our pathology model on a vast dataset faster—securely, and cost-effectively. This enhances EXAONEPath’s processing capabilities for delivering personalized, efficient cancer treatments to improve patient outcomes. EXAONEPath has the potential to transform cancer diagnosis and treatment globally.”
Leveraging Amazon SageMaker, LG AI Research trained and deployed its large-scale EXAONEPath model within eight months, using 285 million data points and more than 35,000 high-resolution tissue sample images. Processing and training AI models with extremely large datasets requires immense storage, high-speed data transfer, and significant compute power. With AWS and NVIDIA GPUs, LG AI Research is accelerating training and inference for its deep learning workloads.
LG AI Research uses Amazon S3 to store and retrieve massive volumes of data that are crucial for research. Amazon FSx for Lustre provides sub-millisecond latencies and delivers hundreds of gigabytes per second of throughput, essential for applications that require rapid access to large datasets. This high-performance file and storage system enables parallel data processing and analysis, significantly reducing the time needed to gain insights.
“The healthcare industry is making rapid progress in its use of AI on AWS to accelerate diagnoses and get patients into treatment faster,” said Dan Sheeran, general manager, Healthcare and Life Sciences at AWS. “Using AWS, LG AI Research can develop and use EXAONEPath at an unprecedented scale, reducing data processing and model training times and improving accuracy. This will allow healthcare providers to improve cancer diagnoses and treatments, reduce wait times, and personalize patient care.”
EXAONEPath is part of LG AI Research’s EXAONE, a 300-billion-parameter multimodal foundation model by LG AI Research, which was also built on Amazon SageMaker and Amazon FSx for Lustre. LG AI Research will continue to update and improve EXAONEPath by training it to detect more types of cancer using additional pathology images.
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About LG AI Research
Launched in December 2020 as the artificial intelligence (AI) research think tank of
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