Mobile phones have become very useful tools in different industries due to their versatility. Thanks to various applications and programs, they can be used for work or games, as well as for the possibility of use in more complex environments, such as in medical centres, as is the case in SpainThe devices found in these places are extremely advanced, sometimes even better than smartphones, but that doesn’t mean phones don’t have a place when it comes to improving patient care.
We have already seen many devices that use smartphones to be more accurate, convenient or cheaper. Now we are seeing how artificial intelligence can change the way research is conducted in some areas of science or how certain medical procedures are performed.
It’s been in the works for years, as news broke in 2018. Now, a software tool created by RMIT University in Australia will allow make it easier to detect cerebrovascular accidents, such as stroke, in secondsmuch faster than is currently possible.
The brain is full of blood vessels that are responsible for delivering blood to all areas of the brain. Their branching and small size means that sometimes blood carries a clot or foreign object from the body to the brain, causing a blockage which leads to the cessation of watering.
This is what is known as a stroke, although They are commonly referred to as stroke or apoplexy.. They can also be the cause of a stroke, caused by an external or internal cause. In essence, this is the same as a heart attack, only localized in the brain.
The fact that this occurs in this organ makes the immediate consequences different from those of other obstacles. For example, Sudden numbness or weakness in the face may often be noticed., especially in the mouth, but also in other parts of the body. It is also normal to feel confused and have difficulty speaking or understanding speech, and walk. This causes dizziness or loss of balance, as well as headache or blurred vision.
The importance of the brain makes it key to detect this type of event quickly, ensuring that the time the organ is without blood supply is as short as possible. A few minutes of delay can mean the difference between permanent damage or not.
A team of biomedical engineers from RMIT University have been working specifically on detecting brain infarctions. using artificial intelligence functions through softwarein a paper in which they explain the use of AI for this type of medical task. Professor Dinesh Kumar is supervising the work, under the direction of Guilherme Camargo de Oliveira from RMIT and the State University of São Paulo.
The professor stressed the importance of this type of tool, as “early detection of stroke is essential as timely treatment can significantly improve recovery outcomes, reduce the risk of long-term disability and save lives.” For this purpose, a a mobile software tool that allows paramedics to instantly determine if a patient has suffered a stroke and report this to the hospital before the ambulance leaves the patient’s home.
This app has an accuracy rate of 82%
but it is not offered as a replacement for existing methods, but rather as an easy-to-use supplement in the early moments of an incident. The ability to detect a stroke early can be critical for a patient, increasing their chances of recovery. This percentage is higher than that of paramedics themselves, when they have to assess at that moment whether a patient has suffered a stroke or not.“Research shows that nearly 13% of strokes go undetected in emergency departments and hospitals, while 65% of patients without a documented neurological examination have an undiagnosed stroke,” said Professor Kumar. In addition, It is important to keep in mind that sometimes the race or gender of the patient can make it difficult to detect a stroke..
The app, which can run on regular mobile devices, allows facial recognition to be used to detect impacts using analysis of facial symmetry and specific muscle movementsso-called action units. The Facial Action Coding System (FACS) classifies facial movements by the contraction or relaxation of facial muscles, providing a detailed basis for the analysis of facial expressions.
It is an analysis system that uses the app’s artificial intelligence to compare each patient’s cases and make a diagnosis. Particular attention is paid to identifying smile asymmetry.one of the most visible indicators that a person is suffering from a stroke. The AI was evaluated using video recordings of facial expressions of stroke survivors and healthy people.
The team’s intention is to turn the smartphone tool into an app in collaboration with other healthcare providers to may detect other neurological conditions that affect facial expressionCollaboration with healthcare providers will be critical to integrating this app into existing emergency response protocols.
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