Machine Learning Helps in Quickly Diagnosis Cases of “New Corona”
Intro to Machine Learning
We hear a lot about the concept of machine learning and its applications in many fields, right? In fact, it is a marvellous magic concept with applications in many different areas, and it is a golden key for a large group of researchers. Unfortunately, in the world we live in, we do not have super solutions that fit everything or solve very complex problems. There are different points of view in books, social media, and Internet sites about the concept of machine learning, its theories, and its applications in various fields. Despite this different perspectives, it has become one of the essential topics that circulate significantly in the scientific and academic milieu, as it has proven its strength and success in solving some issues and problems and drawing actual results that assist many in completing their work perfectly. Machine learning is characterized by giving accurate statistics that help in decision-making (as if it gives advice in determining the correct direction in order to avoid falling). Some people ask a set of questions about machine learning: The first question: Is machine learning artificial intelligence? I can answer this question with yes and no. Machine learning is a subcomponent of artificial intelligence, and it is one of the parts and components of artificial intelligence. The next question is, what will we see when we search online for machine learning applications? My answer will be no comment on this question. I will not include it here, guys. You will explore and browse topics of interest to you using machine learning. Never lose your desire to learn new things. Guys, remember the famous quote by Obi-Wan Kenobi is a character in the Star Wars franchise, “May the Force be with you”, Learning and reading are the evidence of rising to the top — this advice by Maad M. Mijwil to all people trying to advance sciences. To take an example of vehicles, someone wants to buy a vehicle, and after a deep and serious search in the car market, he discovers that the price of vehicles this year is 22 thousand dollars; he also finds that used vehicles, which are one-year-old, cost 18 thousand dollars, while two-year-old cars cost 14 thousand and so on. What we notice here is that the vehicle reduces its price annually by 4 thousand dollars. The lowest price you reach is 10 thousand dollars, for example. This is an example of regression, which is a price prediction based on past information. Here we alert about only two pieces information about the vehicle (the product), which is the price and year, but much other information we must pay attention to, such as the condition of the vehicle, the demand for it, its advantages over others, its type and many other variables, and a normal person cannot know all these things about all vehicles in the market. Here we use the machine, we provide her with the data and information that we have about the products, and we ask her to find all the patterns that are not clear to us. This is why we want to use the machine to solve such a problem, which is prediction.
To perform such a process, we require to utilise a mathematical model that provides the results. Mathematical model always requires simplifications and assumptions as it contains the mathematical equivalent of the interactions in the natural physical practice. In the world we live in, as everything changes at any moment, changes may begin to occur in the system we want to check. If the mathematical model begins to deviate from the natural system, then introducing the control that makes the model happy could lead to natural disaster in the natural system. Well, suppose you train an artificial neural network with these observations of the natural system behaviour. In that case, you might conclude that the artificial neural network becomes a copy of the natural system and may change its behaviour from time to time according to the changes that occur in the natural system, adaptation, that is, if it remains ANN always a current and realistic clone of the physical system … and if you count the control entries accordingly to make this clone happy. If I can train the ANN well i.e., if I create a good copy, then input the control that will make the clone happy will also make the truly happy.
Breadth of COVID’s Impact
Let’s come to the conclusion and link machine learning to our new reality called COVID-19. Studies on the diagnosis of patients with COVID-19 with deep learning, which has recently emerged as a machine learning method, have already begun to be published. The problem primarily exists because machine learning practices historical data to profile behaviours and predict future effects. Suppose the recent behaviours have changed drastically and continue to be volatile. In that case, it makes sense that static machine learning solutions would not stand a chance and would be inaccurate at best and misleading at most critical. Artificial intelligence is beneficial in sharing information about the epidemic situation. For example, information about clinical trials, new insights into how the disease is developing, etc. Data can now be shared in real-time with practitioners such as doctors, medical staff, scientists, and research laboratories worldwide, thanks to artificial intelligence. Any doctor anywhere in the world can now access databases and get the latest ideas in seconds. This is a fantastic contribution. It also definitely helps a lot in the vaccine preparations. We know it has to be tested on animals first and then on humans — and that can’t be done by AI. Machine learning is able to decisively deliver a set of effects in referring pictures of people with COVID-19 disease and comparing them with those with pneumonia and it is able to determine the percentage of virus present in the human lung. Machine learning has a very wide use case across all industries and sectors. However, not all industries or use cases are affected by the data shifts brought about by the Coronavirus. As I evaluate and see around me, only areas where machine learning is being applied to capture consumer/end user behaviour have been affected because that’s the only thing that COVID has changed. So, for example, Alexa has not suddenly stopped understanding English or self-driving cars have not forgotten how to drive because there is no user behaviour here. What has developed is our lifestyle, our daily needs, our online presence, etc.
Machine learning techniques on chest CT scans and the patient’s medical history lead to determining the percentage of a person’s disease with a sensitivity equal to that diagnosed by a chest radiologist.” Researchers explain in the current published studies, “In light of the new Coronavirus invading the world, there is an urgent need for speed Accurate diagnosis of infected cases, which is very necessary. CT-scan is also an important tool in diagnosing patients with COVID-19 infection, but these rays alone are not sufficient to exclude cases of COVID-19 in some patients with other lung diseases. Also, CT-scan results may appear normal for some patients in the early stages of their disease. After seeing many studies, I have found that machine learning models contribute to improving the detection of positive cases of COVID-19 that are made and which were normal CT-scans of their owners, as it helps to modify the diagnosis and correctly detect the rate of infection and determine the strength of the disease. Considering that the accuracy rate of the PCR (Polymerase chain reaction) test, which is used in the diagnosis of COVID-19 patients today, is around 70%, it can be interpreted that the machine learning method will be useful in increasing the diagnostic accuracy, although it may not be used alone, but with other tests. Honestly, there are a lot of topics that I cannot cover at the moment in this simple article, but there are papers that I have made and other papers that I will make on this topic in the future.
