标题: ML in medicine [打印本页] 作者: Nonotusi 时间: 2020-10-12 01:59 标题: ML in medicine Artificial intelligence and machine learning are often confused with each other, but the terms are not entirely interchangeable. Machine learning is a field of data science that is characterized not by direct problem solving, but by learning in the process of applying solutions to many similar problems. Moreover, the algorithm is not programmed according to certain rules. Machine learning technology can reduce the number of people who fail screening. Such solutions enable the identification of patients who are most likely to miss an appointment and will not use radiological treatment. This technology will increase screening coverage. In particular, machine learning can remove random results and can also help detect critical data. And it does it with high accuracy and much faster than specialists. 作者: Mark7 时间: 2020-10-13 01:04
Reinforcement learning is used to solve more complex tasks than teaching and unsupervised learning It is used for example in navigation systems for robots that learn to avoid collisions with obstacles empirically, receiving feedback on each collision作者: Nonotusi 时间: 2020-10-13 01:24
Thanks to the growth in computing power and the emergence of new artificial intelligence technologies, work in this direction has become much more active. There are regular news about the next scientific discovery made with the help of neural networks and machine learning.作者: Mark7 时间: 2020-10-13 02:19
Artificial intelligence technologies are gradually reaching a plateau of productivity; interest is attracted by automated machine learning technologies and business applications with built-in mechanisms. Demand for artificial intelligence platforms provided as a service and related cloud services is growing作者: Nonotusi 时间: 2020-10-13 04:23
Thanks to the growth in computing power and the emergence of new artificial intelligence technologies, work in this direction has become much more active. There are regular news about the next scientific discovery made with the help of neural networks and machine learning. Machines and algorithms can efficiently interpret imaging data by identifying patterns and anomalies.