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Biotechnology and health

This algorithm generates tumors to help fight cancer

September 17, 2018

Researchers have built a system to create a larger and more diverse data set on which to train medical AI.

You’re only as effective as your data set: Most artificial-intelligence programs rely on a large set of information to learn from. But if the data isn’t representative of all populations or circumstances, the system could be biased or ineffective.

The news: A new study out from chip company Nvidia, the Mayo Clinic, and the MGH & BWH Center for Clinical Data Science has created an algorithm that produces a more diverse set of medical data. Using generative adversarial networks (or GANs), synthetic scans depicting abnormalities can be created from existing MRIs of brain tumors.

Why it matters: “Diversity is critical to success when training neural networks, but medical imaging data is usually imbalanced,” Hoo Chang Shin, a research scientist at Nvidia, told ZDNet. “There are so many more normal cases than abnormal cases, when abnormal cases are what we care about, to try to detect and diagnose.”

Deep Dive

Biotechnology and health

The Biggest Questions: What is death?

New neuroscience is challenging our understanding of the dying process—bringing opportunities for the living.

Some deaf children in China can hear after gene therapy treatment

After deafness treatment, Yiyi can hear her mother and dance to the music. But why is it so noisy at night?

Scientists just drafted an incredibly detailed map of the human brain

A massive suite of papers offers a high-res view of the human and non-human primate brain.

Three people were gene-edited in an effort to cure their HIV. The result is unknown.

CRISPR is being used in an experimental effort to eliminate the virus that causes AIDS.

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Illustration by Rose Wong

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