AI System to Generates Synthetic Scans of Brain

These scans are used to teach AI diagnostic system
18 September 2018   1752

A group of researchers developed an artificial intelligence capable of generating sets of images of an MRI of a human brain. The technology is designed to increase the effectiveness of training AI, specializing in the diagnosis of brain cancer. Tests showed that the effectiveness of diagnostic programs trained on generated kits increased by 14%.

The project was implemented jointly by specialists from NVIDIA, the Mayo Clinic and the Clinical Data Research Center. Development based on the generative and adversarial network structure (GAN) was conducted on the NVIDIA DGX platform using the PyTorch deep training systems. Two interconnected artificial intellects were used. One network generated its own MRI snapshots on the basis of real ones, and the second tried to distinguish real from fake ones.

GAN automatically marks the created sets of MRI images, which significantly speeds up learning. With manual annotation, this work takes experts many hours. In addition, since the system does not consider the brain and tumor as a whole, the operator can correct the picture by moving the tumor or changing its size.

Hu Chang, one of the authors of the study, said that the generated MRI kits also solve the problem of using confidential information. These pictures form a medical secret, and permission is required to use them. And the resulting system can be publicly available.

Hardware limitations forced the team to reduce the resolution of the original images by 8 times. Also, at the moment, neoplasms sometimes look "superimposed" on a snapshot. In the future, researchers plan to eliminate these shortcomings.

When teaching neural networks-diagnosticians, the question of the availability of training datasets is relevant. Developed by German scientists, AI, which determines myocardial infarction by ECG, used as input only 200 records. According to the creators, this seriously worsened the efficiency of the system. Tools that create datasets for learning neural networks are designed to help solve this problem.

BNC to Monitor BTC Community's Mood

The system called Twitter Sentiment analyzes over 34M BTC-related Twitter posts each week, using AI to track the mood of the community
22 January 2020   468

Blockchain-based New Zealand-based research firm Brave New Coin (BNC) has unveiled a new system for measuring the mood of the Bitcoin community based on Twitter messages.

According to BNC, the new Twitter Sentiment rating system analyzes over 34 million BTC-related Twitter posts each week. The company uses artificial intelligence (AI) algorithms that look for records containing the words bitcoin, $ BTC and BTC and others.

BNC notes that user sentiment continues to be a “significant” factor in the price and dynamics of digital assets, and a new technique has been developed to track these sentiments. According to the BNC, it took 18 months to launch the Bitcoin Twitter Sentiment. The data obtained is divided into seven categories - Opinion, Technical Information, Inside the Network, Advertising, Bots, Macros and Hacking.

For the week ending January 17, the most common entries were in the Opinion category - their number was 30.42% of all data received. In second place was the category Technical Information, and in third inside the network (includes information on mining and hashrate).

BNC spokeswoman Pierre Ansaldi said that during the first quarter of this year, the company will also launch community sentiment analysis tools for other crypto assets.