CapeStart helped a major multinational digital health company develop a multi-omic, AI-powered classifier to predict patient responses to checkpoint inhibitors. Checkpoint inhibitors are a class of immuno-oncology agents often used to treat solid tumors.
The client needed a reliable, knowledgeable, experienced and affordable partner to analyze and label a large batch of de-identified multislice CT images. This data would then be used to train and validate the AI classifier, which would be used to drive better health outcomes for patients using checkpoint inhibitors.
Download the case study to learn how the CapeStart team’s extensive experience working in multislice PET scans – along with its innovative data labeling tool, ProNotate – helped them quickly identify and annotate images of cancerous lesions in the lungs.
Meet the Presenters
Kavin Xavier
Vice President – AI Solutions, CapeStart
With years of experience designing AI solutions for life sciences, Kavin leads CapeStart’s AI innovation roadmap.
Siva Karthick
Machine Learning Tech Lead, CapeStart
Siva specializes in model fine-tuning and evaluation, focusing on real-world deployment of AI in healthcare and pharma.
