In 1966, etoposide was approved as the primary drug for small cell lung cancer treatment. 50 years later, a study revealed that the drug severely compromised the immune systems of 92% of Japanese patients. That statistic was only 66% in Caucasian populations, on whom the drug was initially tested. Had the data on Japanese populations been released for research sooner, countless deaths could have been prevented.
It’s time we start sharing.
Currently, privacy concerns prohibit patient data sharing across hospitals. Using machine learning, we’ve built a platform to democratize access to global medical data, while keeping patient medical information private.
In our implementation of federated learning, each hospital trains a model on data from their patient populations The updates from those versions are aggregated to form a powerful model that leverages insights from a diverse range of patient data
We're breaking down data silos to enable medical breakthroughs with global relevance.
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