AI to Diagnose Eye Diseases

The system was developed in connection with the Moorfields Eye Hospital
15 August 2018   1539

The British company DeepMind has introduced a system that, based on the optical coherence tomography (OCT) image of the retina, identifies up to 50 eye diseases.

The system was developed in conjunction with the Moorfields Eye Hospital - its doctors make over a thousand OCT images every day. The specialists take a lot of time to process even one - sometimes this leads to the fact that the disease progresses and causes irreversible changes in the visual organs.

OCT Analysis
OCT Analysis 

The new algorithm allows to reduce the analysis time to several seconds. It is based on two neural networks. The first - the segmentation network - converts the original OCT images into a tissue map. It distinguishes features of diseases and their hearth: hemorrhage, damage and so on. The second neural network - classification network - analyzes a 3D map and diagnoses it. The system not only represents the accuracy of the analysis as a percentage, but it also prioritizes the treatment and gives its recommendations.

The algorithm was trained on a set of 15 thousand pictures from 7,5 thousand patients, accompanied by diagnoses of doctors. The main difference between the development of DeepMind and similar ones is that the system reflects how it came to some conclusions. In addition, it works with any type of images - it will allow using it in any medical center.

Now the algorithm is being clinically tested in Moorfields Eye Hospital. According to its creators, it can take 3-5 years. In case of successful results, the system will be used by 30 more medical centers and clinics throughout the country.

In February 2018, scientists from Google and a subsidiary of medical company Verily discovered a new method that predicts heart disease with the help of machine learning. Based on the scan of the retina, the system provides accurate patient data: age, blood pressure, addictions.

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   480

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.