📌Google teaches the neural network to predict the death of a person📌

🔬Modern medicine is aimed at preventing and anticipating the development of serious life-threatening diseases. However, the strength and knowledge of a person is often not enough to predict certain complications. 🔬
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"To help doctors in the future may come AI DeepMind from Google, which is currently learning to predict the death of people.
As is often the case in this situation, already known clinical cases have been used to teach AI.📢
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📈Information about patients was provided by the medical center of the University of California at San Francisco and the Medical University of Chicago. In addition, the scientists used information obtained from the US Veterans Affairs Department, which gave access to data on 700,000 under the supervision of former military personnel. A total of more than 46 billion items on the most varied health indicators were included in the database.📈
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📡The system is now capable of predicting a patient's death within 24-48 hours, but the main goal of the project is to learn how to predict death in the next 12 months. In addition, it is planned to expand data on deadly pathological conditions. Such use of artificial intelligence for medical purposes can be used not only to be ready for resuscitation, but also to prevent the development of severe conditions in patients. University of California at San Francisco and the Medical University of Chicago. In addition, the scientists used information obtained from the US Veterans Affairs Department, which gave access to data on 700,000 under the supervision of former military personnel. In total, more than 46 billion items on the most varied health indicators were added to the base.
Now the system is capable of predicting a patient's death within 24-48 hours, but the main goal of the project is to learn how to predict death in the next 12 months. In addition, it is planned to expand data on deadly pathological conditions. Such use of artificial intelligence for medical purposes can be used not only to be ready for resuscitation, but also to prevent the development of severe conditions in patients.📡