Identifying a color is an easy task, shine a wavelength of 620 nano-meters and most people will say it looks red. But when it comes to figuring out how exactly a particular molecule will smell, complexity gets increases to the next level, both for humans and machines too.
The one reason it is so hard to identify the smell of a particular molecule is that there is no intermediate carrier of smell, like for sound we have a vibration in the air.
Now, a team of scientists has developed a deep learning method that smells compounds in the human breath and detects illnesses. The AI can detect 17 diseases, including 8 different types of cancer, just from your breath.
This AI is cable of recognizing chemical signatures of the diseases by their chemical structure.
It is created by an international team of researchers from 5 countries universities -Loughborough University, Western General Hospital, the University of Edinburgh, and the Edinburgh Cancer Centre in the United Kingdom.
The project was led by Professor Hassam Haick of the Technion-Israel Institute of Technology. The team is now developing Sniffphone for disease detection right through your smartphone.
“The sense of smell is used by animals and even plants to identify hundreds of different substances that float in the air. 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.” he further added.
This device carries a sensor called nano-array which is controlled by AI software. It is made up of carbon nanotubes and tiny gold particles. Its 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 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. The scientists used mass spectrometry to figure out a 13-component “breath print” for each of the 17 diseases in the study.
The team first collected the breath samples from participants undergoing cancer treatment. The samples were then analyzed by two teams of chemists and computer scientists. After the number of compounds was identified manually by the chemists, the data then passed to deep learning networks, so they can get trained.
With every breath sample, AI starts to learn more efficiently, soon it starts 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.
The convolutional neural network dataset was augmented 100 times.
We found that just as we each have a unique fingerprint, each of the diseases we studied has a unique breath print, a ‘signature’ of chemical components,” said Professor Haick. “We have a device which can discriminate between them, which is elegant and affordable.”
Breath is an excellent raw material for diagnosis,” Professor Haick told Haaretz. “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. Crohn’s disease and kidney disease. The AI devise tested on 2,800 breath samples from 1,404 people in the U.S., Israel, France, Latvia, and China and was able to correctly diagnose in almost 9 out of cases.
It’s the first time a device was created that can distinguish between different diseases in a breath sample. Artificial intelligence plays a large role in that. Professor Haick, a nanotechnology expert, explained its workings this way to Smithsonian.com:
Haick said their AI “nose” can be used in other industries as well, like security or quality control.
“Computers equipped with this technology only take minutes to autonomously analyze a breath sample that previously took hours by a human expert,” Soltoggio said. AI is making the whole process cheaper – but above all, t is making it more reliable.
Scientists are testing the device on thousands of patients so it can give an accurate result. Application of this device to the -world hospital is a future thing as it is still in a development process, but the archer ensures that it will soon get launch in the et,
They think making this technology widespread could really impact the survival rates of patients with certain diseases by allowing for much earlier detection.
The work will be presented at the International Joint Conference on Neural Networks (IJCNN 2018), Rio de Janeiro, Brazil next month. The research paper was recently published on Research Gate.
You can read the study here, in the American Chemical Society Nano journal.
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