Imagine that the chip is even more powerful than the best laboratories in the world and can quickly diagnose the disease accurately. A miniature camera can test the trueness and falseness of a Tablet at the molecular level. The system can detect that a person has mental illness from the language. IBM believes that these three things can be done within a few years because they have big killers: artificial intelligence + new hardware.
IBM Research has begun to turn these three studies into a mature medical tool that combines the company’s existing machine learning and artificial intelligence systems with silicon and millimeter wave phased array sensors.
AI+ super imaging system, "look" to diseases and hazards
The "super-imaging system" to be mentioned first is a wide-range electromagnetic spectrum imaging technique that can not only acquire images formed by the visible light of human eyes but also simulate electromagnetic wave images beyond this range.
Using high-performance cameras and other sensors, clinicians can find out if the medication is suitable for the patient. "Using this kind of super-imaging technology, people are like a third eye, and they can find clues that we ignore every day," said Rashik Parmar, IBM's technical director.
Although hardware to implement ultra-imaging has emerged, more work needs to be done to get it into the market. Instruments that can perform a wide spectrum of spectral imaging are nothing new, but the difference is that IBM will simplify, miniaturize, and reduce its manufacturing costs. It will also use cognitive algorithms to decipher and visualize, and let this technology really play its role. .
Parmar also added that IBM now has a lot of "fancy" inventions, but it can quickly turn them into more usable products. In medical applications, a simple example is using super-imaging equipment to quickly see the teeth, or to provide more information for standard medical ray inspection.
Probably within five years of IBM’s plan, this machine will become a pharmacology and toxicology expert around you—ultimately, this kind of super-imaging will be integrated into the cell phone and you can scan it before eating or taking medicine. , to see if there are harmful substances or sources of sensitization.
AI+ Chip Lab, Precise Diagnosis of Premature Diseases
Similarly, IBM may also launch a new artificial intelligence analysis technology within a few years: the chip lab. This device is also the size of a purse, with a drop of blood or any body fluid to analyze bacteria, viruses, or proteins that herald a disease.
"Lab Lab" (Source: IBM Research)
Parmar said that IBM began exploring the concept of "nanofibers" six or seven years ago. It was time to do a tool that could simulate odors.
If nanofibers are combined with other types of sensors, nanostructures can be used to test body fluids, including saliva, blood, and liquid biopsy samples, to analyze potential diseases. Combined with technologies such as digital manufacturing and 3D printing, IBM can place sensors in custom probes to help with effective analysis.
Compared to the need to wait a few weeks for blood tests, the chip lab does not have to spend time growing the virus up to the amount that can be monitored, but instead tracks the most subtle biomarkers directly through the sensor.
Perhaps the most powerful thing about this technology is that it allows people to understand their illness before they develop symptoms. To give an example of Alzheimer's disease, the patient's nervous state has changed significantly for a long period of time before the apparent symptoms appear.
If you regularly check blood samples, you can look for biomarkers early in Alzheimer's disease and quickly start developing treatment plans based on your individual circumstances.
Although this technology that can analyze disease from a single drop of blood is a huge challenge to the level of artificial intelligence, the true test of IBM's introduction of this kind of product to the market lies in silicon wafers with high technical difficulty. "The chip's minimum measurement level is 20 nanometers. It allows you to observe viruses and other substances from a very detailed perspective, but to see this level of detail, it takes a lot of effort to make materials."
AI+ text information to form a mental illness model
Mental illness is yet another area that requires artificial intelligence technology to chew large amounts of data and turn it into effective medical insights. In the next two years, IBM will create prototypes of machine learning systems that can diagnose mental illness from human speech.
In the diagnosis of mental illness, patient's conversation has always been an important factor used by doctors to judge the condition. Speed, volume, and language features can all be used to judge mental illness. Now that IBM has given this analysis work to artificial intelligence, communication from patients and doctors, or people's own words written on social networking websites, can be used as analysis materials.
IBM can do this, provided that they have spent years researching the connection between mental and psychological disorders and language and have established a measurement system. "We are currently studying the agenda to clarify this matter: For certain individuals, can certain words in a paragraph of speech help us understand the person's mental state?" said technical director Parmar.
IBM has long had an attempt to establish a medical model: Watson's earliest attempts at commercialization, and the "Blue Giant" cognitive computer system is the assistant to a cancer care physician. Today, the company has also had a lot of cooperation with the medical industry to establish a variety of prototypes of medical awareness tools.
For example, IBM disclosed that Jupiter Medical Center (Jupiter Medical Center), Florida's local medical center, will introduce IBM Watson's tumor-assisted medical technology. In addition, it cooperated with the Memorial Sloan Kettering Cancer Center (MSK) in a cancer therapy training program.
In addition to schizophrenia, bipolar disorder, depression, etc., IBM will also obtain data from wearable exercise equipment and medical equipment to assist in the diagnosis of neurological diseases such as Parkinson's disease. Although medical health experts now use wearable data for diagnostic judgment, IBM hopes to use machine learning to accelerate this process and provide additional insights.
Parmar said that in fact, some people in the United States and Europe have done experiments on wearable data, and some professors have shared experimental data. However, no one has combined these data to study whether there is any correlation between these data, or to use integration. The data yields a deeper understanding. "Using machines to process and integrate is precisely the answer to this question."
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