Application of Machine Learning in Artificial Intelligence
What do you think about artificial intelligence? Is that really true? Often when we do something we do not like to do, the thought "Wouldn't it be nice to have a machine to do this?"
In the 21st century, at a time when we are preparing for another industrial revolution, one of its main topics is machine learning using artificial intelligence. Man, the world's most intelligent being, is now reaping the full benefits of technology. If a machine can think like us, how good is it? Nowadays with machine learning, many innovations are created day by day using artificial intelligence. Now the world is approaching to use it as a nerve wave input and the technology has evolved from mechanical devices and tactile systems. The development of computer programs that can access data through machine learning has already been completed for many fields such as health, agriculture, medicine, transportation, mechanics, and education etc...
We must now think not of its predecessors, but of a new application that can be done using machine learning. If this is the correct answer to a current problem, it is the success here. Currently, 4% (275 million) of the global population suffers from anxiety disorders due to overwork. It covers 2.5% to 6.5% of a country's population. A recent meta-analysis revealed that mood and anxiety disorders cause nearly 5 million deaths worldwide each year.
How many lives could be prevented from being lost prematurely if proper treatment were given for this? We can offer a solution to this by applying machine learning in AI. There is already treatment for this, and the problem is that very few people seek treatment for the disease. But by learning the machines of AI into the lives of those who lose their lives prematurely without recognizing this Properly covered, it will withstand plenty of adverse conditions. The challenge is to identify those who have the disease. Anxiety can be affected by low delta and theta waves, which are associated with a decrease in alpha waves and an increase in beta waves.
Corona, a crisis we all face globally these days, is used to measure everyone's body temperature during daily activities in all countries of the world. We can use machine learning to identify the alpha and beta wavelengths emitted by our brain along with body temperature and identify people with anxiety. Small oscillating voltages with amplitudes ranging from microvolts to a few millivolts are called brain waves. Today, EEG technology is used for this purpose in medical science. The main purpose of this is to identify those who are not tempted to seek treatment and to refer them for the treatment they need. I am confident that the above method will provide a solution. For this purpose, an application can be used to identify the wavelengths of the alpha and beta rays emitted by the brain, analyze their wavelengths, and identify different frequencies than the specific frequency.
Understanding and interpreting electrical patterns in the brain, which is an extremely challenging task, is great hope for neuroscientists and neurobiologists. An electroencephalogram (EEG) is a test that uses small metal disks (electrodes) attached to your skull to detect the electrical activity of your brain. Utilizing this tool, it is possible to easily diagnose diseases such as anxiety by analyzing the frequency of radiation emitted by the brain without having to undergo a specialized medical examination and to provide appropriate medical treatment and advice. Using machine learning it is possible to perform automatic clinical EEG analysis and obtain test results instantly.
As mentioned above, this can also be combined with a body temperature monitor so that both functions can be performed simultaneously. There is no doubt that in the near future, a successful solution can be found by learning machines using artificial intelligence to reduce the number of untimely deaths due to such mental illnesses.
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