Australia risks losing its world-leading advantage in critical and rare minerals used for clean energy, electric vehicles and batteries for solar energy, unless it embraces artificial intelligence in the mining
An ideal AI system should minimize the number of false results. We expect more studies to investigate how this happened and to find strategies to minimize errors. Our study has several limitations. First, two-dimensional images rather than three-dimensional images were used to train the deep ...
This work aimed to use artificial intelligence to predict subjective refraction from wavefront aberrometry data processed with a novel polynomial decomposition basis. Subjective refraction was converted to power vectors (M, J0, J45). Three gradient boost
ADM: What is Artificial Intelligence, and how are organizations applying AI to the software development life cycle (SDLC)? Weishaar:We’ve been using Forrester’s definition of AI lately. It reads, “A system, built through coding, business rules, and increasingly self-learning capabilities, that...
relatively limited research efforts have been made to develop artificial intelligence (AI) and machine learning (ML) oriented FNaD detection models suited to minimize supply chain disruptions (SCDs). Using a combination of AI and ML, and case studies based on data collected from Indonesia, Malaysia...
Learning how people interact with artificial intelligence-enabled machines—and using that knowledge to improve people's trust in AI—may help us live in harmony with the ever-increasing number of robots, chatbots and other ...
Using artificial intelligence (AI) in healthcare may seem cutting edge, but the technology has actually been around for decades. Research suggests theearliest incarnation of AI—the simulation of human intelligence in computers—dates back to the 1950s. Granted, the limitations of early models preve...
ECGs were labeled as case=1 or control=0 and the model was trained to minimize the binary cross entropy between model prediction and the label using RMSprop optimizer with initial learning rate of 0.0001. The model was trained for 150 epochs. At the end of each epoch, C-statistics on the...
Given EmbryoNet’s performance in identifying subtle phenotypes, we hypothesized that we could leverage artificial intelligence to detect very early embryonic defects before they would be recognized by human experts. We therefore retrained EmbryoNet by moving the relevant developmental timepoint corresponding...
Waves of disruption have been felt across the electricity industry as the digitalization journey in this sector has converged with advances in artificial intelligence (AI). However, there are risks involved. As AI becomes more established, new security threats have emerged. Among the most important ...