2 ways Al is preventing strokes in 2023 and the companies behind each breakthrough.
Can machines think? – Alan Turing, 1950
A question that has changed the point of view of the world. In the meantime, AI aims to answer Turing’s question. The purposes of artificial intelligence are too many that AI has no certain definition. However, it is described as the technological simulation of human intelligence by computer machines. AI has succeeded in many ways in improving the medical field. Either by preventing a certain disease or helping healthcare professionals detect it. In many cases, AI could do the task better than humans, artificial intelligence is now used in surgeries and is mandatory in the place of work.
AI in 2023 can help prevent strokes in two ways.
Using AI to predict a stroke
According to the centers for disease control and prevention (CDC), stroke causes huge pressure on U.S. healthcare, it costs billions yearly for different reasons such as medications and missed work days. Researches show that AI algorithms Can detect early diagnosis of atrial fibrillation using a specific type of rhythm electrocardiograph, AI also screens the possibility of risk in the population. Recently, there has been a machine model for predicting short-term probabilities with acute ischemic stroke, this has better outcomes than the traditional. The CDC states that strokes have a high percentage of prevention, only if predicted at the right time, this makes artificial intelligence necessary.
Behind this breakthrough : Google studies and American stroke association.
Using AI to Support Decision-Making in Stroke
Making a decision for one's future requires the human intellect to deal with a lot of information. On the other hand, AI algorithms have no upper bound. We believe that early, accurate diagnosis (as discussed) and timely treatment—which refers to the intelligence of machines— are necessary to raise the rate of stroke prevention. According to a CNN study, deep learning-based systems are 150 times faster than radiologists at detecting acute neurological events in cranial imaging. Neuroimaging data, which is used in stroke research and clinical care, can be properly detected by AI.
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