AI case studies from the real-world

NYU researchers detected lymphedema with 93.8% accuracy using neural networks

National University of Singapore researchers use deep learning to outperform current methods in detecting glaucoma progression in patients

Newcastle University researchers automate identification of grip type needed to pick up objects by prosthetic limb with 88% success

Nvidia restores images by only looking at corrupted examples using machine learning

Oregon Health and Science University trained deep learning models on used machine learning to diagnose the leading childhood blindness disease with 91% accuracy bettering the 82% of opthalmologists

Particle physicists carry out complex analyses on the 1 million gigabytes of data produced per second during experiments using machine learning.

Researchers aim to identify fibromyalgia patients from fMRI images using machine learning

Researchers at Harvard University and the University of Tübingen track animals’ movements in the lab using deep learning

Researchers at IBM Research Australia, the University of Toronto, and University of Melbourne build model to generate sonnets using deep learning

Researchers at Los Alamos National Laboratory identified a sound pattern that indicates slippage and fault failure using machine learning

Researchers at MIT have developed a new deep neural network algorithm that can identify people by detecting movements across walls using Wifi signals with ~83% accuracy

Researchers at Tomsk Polytechnic University Russia to launch a fleet of robot-bee prototypes suitable for greenhouses

Researchers at UC Berkeley find 72 previously undetected bursts in data gathered on FRB 121102 using machine learning

Researchers at University of Washington explore diagnosis of early onset of pancreatic cancer by identifying increased bilirubin levels in sclera from selfies with 89% accuracy

Researchers at the University of Glasgow develop platform to locate new molecules using machine learning

Researchers detect restaurants with elevated risk of foodborne illness in real time using machine learning

Researchers from Boston University improve automatic parameter selection for synthetic data creation

Researchers from MIT train AI to predict recipe ingredients by looking at a photo of food using machine vision and deep learning

Researchers improve film box office success prediction using machine learning transduction algorithms

Researchers in South Korea demonstrate accuracy of 98.8% in diagnosing Parkinson's disease using convoluted neural networks

Rice University researchers are developing an application that writes Java API code snippets using deep learning

Scientists aim to eliminate animal testing by automating the proccess based on existing knowledge about chemical interactions using machine learning

Scientists at the Francis Crick Institute outperform medical models at predicting risk of death in patients with heart disease using machine learning

Scientists develop an artificial neural network that can identify handwritten numbers and molecular handwriting

Scientists produce the largest photogrammetric map of one of the best studied gas hydrate deposits with the use of autonomous underwater vehicles and unsupervised learning

Stanford University Medical uses deep convolutional neural networks to predict skin cancer as well as dermatologists

Stanford University Parker Institute for Cancer Immunotherapy predict childhood leukemia patients relapse with 85% accuracy using machine learning

Stanford University trained deep neural networks to predict skin carcinomas from images with the same accuracy as determatologists

Sun Yat-sen University researchers predict high myopia for young adults at clinically acceptable levels 8 years in advance

The University of Alberta aims to ensure the safety and independence of seniors using deep learning and machine vision