AI News, Shape Created with Sketch. In pictures: Artificial intelligence through history

Shape Created with Sketch. In pictures: Artificial intelligence through history

Artificial intelligence (AI) is best known for its ability to see (as in driverless cars) and listen (as in Alexa and other home assistants).

For this reason, humans aren’t particularly aware of the richness of information that can be transmitted through the air, and can be perceived by a highly sensitive olfactory system.

Those machines, called gas-chromatography mass-spectrometers or GC-MS, can analyse the air to discover thousands of different molecules known as volatile organic compounds.

The sheer amount of compounds and the complexity of the data mean that even experts take a long time to analyse a single sample.

As part of Loughborough University’s data science team, my colleagues and I are adapting the latest artificial intelligence technology to perceive and learn a different type of data: the chemical compounds in breath samples.

Mathematical models inspired by the brain, called deep learning networks, were specifically engineered to “read” the traces left by odours.

team of doctors, nurses, radiographers and medical physicists at the Edinburgh Cancer Centre collected breath samples from participants undergoing cancer treatment.The samples were then analysed by two teams of chemists and computer scientists.

Once a number of compounds were identified manually by the chemists, fast computers were given the data to train deep learning networks.

Using this technique, deep learning systems can be trained to detect small amounts of volatile compounds with potentially wide applications in medicine, forensics, environmental analysis and others.

Artificial Intelligence May Be Able To Smell Illnesses in Human Breath

Artificial intelligence (AI) is best known for its ability to see (as in driverless cars) and listen (as in Alexa and other home assistants).

For this reason, humans aren’t particularly aware of the richness of information that can be transmitted through the air, and can be perceived by a highly sensitive olfactory system.

Those machines, called gas-chromatography mass-spectrometers or GC-MS, can analyze the air to discover thousands of different molecules known as volatile organic compounds.

The sheer amount of compounds and the complexity of the data mean that even experts take a long time to analyze a single sample.

As part of Loughborough University’s data science team, my colleagues and I are adapting the latest artificial intelligence technology to perceive and learn a different type of data: the chemical compounds in breath samples.

team of doctors, nurses, radiographers and medical physicists at the Edinburgh Cancer Centre collected breath samples from participants undergoing cancer treatment.

Once a number of compounds were identified manually by the chemists, fast computers were given the data to train deep learning networks.

The deep learning networks learned more and more from each breath sample until they could recognize specific patterns that revealed specific compounds in the breath.

Using this technique, deep learning systems can be trained to detect small amounts of volatile compounds with potentially wide applications in medicine, forensics, environmental analysis and others.

AI and the Summit GPU-Accelerated Supercomputer Helps Identify Extreme Weather Patterns

Researchers from Loughborough University, Western General Hospital, the University of Edinburgh, and the Edinburgh Cancer Centre in the United Kingdom, recently developed a deep learning-based method that can analyze compounds in the human breath and detect illnesses, including cancer, with better than-human average performance.

“For this reason, humans aren’t particularly aware of the richness of information that can be transmitted through the air, and can be perceived by a highly sensitive olfactory system.” Using NVIDIA Tesla GPUs and the cuDNN-accelerated Keras, and TensorFlow deep learning frameworks, the team trained their neural network on data from participants with different types of cancer receiving radiotherapy, said researcher Angelika Skarysz, a PhD research student at Loughborough University.  To increase the neural network’s efficiency, the team increased the original training data by using data augmentation.

Scientists Invent An AI That Can Smell 17 Diseases From Your Breath, Including Cancers

Identifying a color is a easy task, shine a wavelength of 620 nano-meters and most people will say it looks red.

But compared to that of other animals, the human sense of smell is far less developed and certainly not used to carry out daily activities,” researcher Andrea Soltoggio wrote on Smithsonian.com.

“For this reason, humans aren’t particularly aware of the richness of information that can be transmitted through the air, and can be perceived by a highly sensitive olfactory system.” This devise carries a sensor called nano-array which is controlled by AI software.

It’s deep learning algorithm is capable of analyzing the human breath samples form the special chemical signatures that correspond to various diseases.

This system works because an average people exhale over a 100 unique chemicals called volatile organic compounds (VOCs). The team proved that each disease has a very specific chemical signature within a person’s VOC.

With every breath sample, AI start to learn more efficiently, soon it start to recognize specific patterns that revealed specific compounds in the breath. To increase the neural network’s efficiency, the team increased the original training data by using data augmentation.

“It is available without the need for invasive and unpleasant procedures, it’s not dangerous, and you can sample it again and again if necessary.” Besides cancers, the conditions the device can diagnose include Parkinson’s, multiple sclerosis.

Application of this devise to real world hospital is a future thing as it is still in a development process, but researcher insures that it will soon get launch in market, They think making this technology widespread could really impact the survival rates of patients with certain diseases by allowing for much earlier detection.

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