All posts tagged: detection

AI could revolutionise glaucoma detection. Here’s 6 things everyone should know

AI could revolutionise glaucoma detection. Here’s 6 things everyone should know

Published by Daniella Wilson

Artificial intelligence could revolutionise the detection of glaucoma, a common eye condition, while significantly reducing the number of unnecessary specialist referrals, a new study suggests. Published in the Lancet Primary Care, the research from Portugal involved an AI tool analysing eye images from 671 individuals aged between 55 and 65. The technology demonstrated superior accuracy, correctly identifying 78 per cent of people with glaucoma, compared to 75 per cent detected by human doctors. Furthermore, the AI proved more effective at ruling out the condition, accurately excluding 95 per cent of those without glaucoma, against 91 per cent by medical professionals. Crucially, the AI tool recommended just 66 individuals for specialist consultation, leading to 40 glaucoma diagnoses, a stark contrast to the 118 referrals made by eye doctors, which ultimately resulted in the same number of diagnoses. This significant advancement suggests a future where AI could streamline diagnostic processes, ensuring earlier detection for patients and simultaneously alleviating pressure on specialist eye clinics. open image in gallery (Alamy/PA) 1. Glaucoma is a group of eye diseases “Glaucoma …

Different Bubbles, Different Methods of Detection: What of AI?

Different Bubbles, Different Methods of Detection: What of AI?

Published by Jenni Sidey

Financial bubbles involving inflated share prices have occurred many times over recent centuries. But how do we detect inflated share prices? It depends on the nature of the bubble. Bubbles and bursts The Wall Street Crash of 1929 was due to excessive capacity in factories across the U.S. Investors overestimated the extent to which consumers would buy the rapidly increasing output. The resulting Great Depression, which led to widespread unemployment, also resulted in an emphasis on price-to-earnings ratios. The measurement was made in order to detect bubbles by comparing stock prices to earnings. The dotcom bubble of 2000 revolved around the companies expected to benefit most from the internet economy. These were the largest companies in the Nasdaq Index such as Cisco, Microsoft, Lucent, Nokia, IBM, Oracle, AT&T, and Intel (despite the name “dotcom”). The value of the Nasdaq thus became a new barometer of bubbles. How the AI bubble differs from the dotcom bubble The AI bubble revolves around a much smaller number of companies, particularly OpenAI, a privately held firm that has no …