What has Artificial Intelligence done for radiology lately in 21st Century?

Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Artificial Intelligence (AI), sometimes called machine intelligence, is Computer systems theory and engineering capable of performing tasks that typically require human intelligence, such as visual processing, speech recognition, decision-making, and language translation. To further expand this concept of AI in the scope of radiology results in "a computer science unit dealing with the processing, reconstruction, analysis and/or analysis of medical images by simulating intelligent human behavior in computers." Radiology, also defined as diagnostic imaging, is a series of different tests that take images of different parts of the body. Radiologists perform a wide array of diagnostic tests, including x-rays, ultrasound, densitometry of bone minerals, fluoroscopy, mammography, nuclear medicine, CT, and MRI.