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Now AI Can Identify Microscopic Marine Organisms

"This work demonstrates the successful first step toward building a robotic platform that will be able to identify, pick and sort forams automatically," Lobaton noted

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Artificial Intelligence Bot
Artificial Intelligence Bot. Pixabay

Researchers have developed an Artificial Intelligence (AI) programme that can automatically identify microscopic marine organisms, according to a new study.

The study showed that specifically, the AI programme has proven capable of identifying six species of foraminifera or forams — organisms that have been prevalent in Earth’s oceans for more than 100 million years.

“At this point, the AI correctly identifies the forams about 80 per cent of the time, which is better than most trained humans,” said Edgar Lobaton, Associate Professor at the North Carolina State University.

“We also plan to expand the AI’s purview, so that it can identify at least 35 species of forams, rather than the current six,” said Lobaton.

Cell Pattern, Artificial Intelligence
Artificial intelligence through machine learning can detect complex patterns in cell arrangement that would be difficult for humans to recognize. VOA

The current system works by placing a foram under a microscope capable of taking photographs. An LED ring shines light onto the foram from 16 directions — one at a time — while taking an image of the foram with each change in light.

These 16 images are combined to provide as much geometric information as possible about the foram’s shape.

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The AI then uses this information to identify the foram’s species, said the study, published in the journal Marine Micropaleontology.

“This work demonstrates the successful first step toward building a robotic platform that will be able to identify, pick and sort forams automatically,” Lobaton noted. (IANS)

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Researchers Can Now Detect Heart Failure with 100% Accuracy with the Help of Artificial Intelligence

Conversely, their new model uses a combination of advanced signal processing and machine learning tools on raw ECG signals, delivering 100 per cent accuracy

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Artificial Intelligence Bot
Artificial Intelligence Bot. Pixabay

With the help of Artificial Intelligence(AI), researchers have developed a neural network approach that can accurately identify congestive heart failure with 100 per cent accuracy through analysis of just one raw electrocardiogram (ECG) heartbeat.

Congestive heart failure (CHF) is a chronic progressive condition that affects the pumping power of the heart muscles. Associated with high prevalence, significant mortality rates and sustained healthcare costs, clinical practitioners and health systems urgently require efficient detection processes.

The researchers have worked to tackle these important concerns by using Convolutional Neural Networks (CNN) – hierarchical neural networks highly effective in recognising patterns and structures in data.

“We trained and tested the CNN model on large publicly available ECG datasets featuring subjects with CHF as well as healthy, non-arrhythmic hearts. Our model delivered 100 per cent accuracy: by checking just one heartbeat we are able detect whether or not a person has heart failure,” said study researcher Sebastiano Massaro, Associate Professor at the University of Surrey in the UK.

artificial intelligence, nobel prize
“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

“Our model is also one of the first known to be able to identify the ECG’ s morphological features specifically associated to the severity of the condition,” Massaro said.

Published in Biomedical Signal Processing and Control Journal, the research drastically improves existing CHF detection methods typically focused on heart rate variability that, whilst effective, are time-consuming and prone to errors.

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Conversely, their new model uses a combination of advanced signal processing and machine learning tools on raw ECG signals, delivering 100 per cent accuracy.

“With approximately 26 million people worldwide affected by a form of heart failure, our research presents a major advancement on the current methodology,” said study researcher Leandro Pecchia from the University of Warwick. (IANS)