Graphene puts nanomaterials in their place

Nanomaterials offer unique optical and electrical properties and bottom-up integration within industrial semiconductor manufacturing processes. However, they also present one of the most challenging research problems. In ...

Painting a clearer picture of the heart with machine learning

Coronary artery disease (CAD) is a condition in which plaque forms on the walls of coronary arteries, causing them to narrow. Eventually, this could lead to a heart attack, or death. This condition is now the single largest ...

Helping to improve medical image analysis with deep learning

Medical imaging creates tremendous amounts of data: many emergency room radiologists must examine as many as 200 cases each day, and some medical studies contain up to 3,000 images. Each patient's image collection can contain ...

No farms, no food

Agriculture consumes more than 70 percent of the world's annual water usage. With small farms producing nearly 80 percent of food for the developing world, ensuring the quality and safety of our water supply is critical. ...

Semantic cache for AI-enabled image analysis

The availability of high-resolution, inexpensive sensors has exponentially increased the amount of data being produced, which could overwhelm the existing Internet. This has led to the need for computing capacity to process ...

AI for code encourages collaborative, open scientific discovery

We have seen significant recent progress in pattern analysis and machine intelligence applied to images, audio and video signals, and natural language text, but not as much applied to another artifact produced by people: ...

Teaching AI to learn from non-experts

Today my IBM team and my colleagues at the UCSF Gartner lab reported in Nature Methods an innovative approach to generating datasets from non-experts and using them for training in machine learning. Our approach is designed ...

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