Ever wonder how self-driving cars recognize a ball in the road? How about when Amazon magically knows what items you need before you do? This is all thanks to pattern recognition of artificial intelligence (AI). Analytical AI refers to the general process by which machines or computers replicate and replace human tasks and cognition. Machine learning is a branch of AI in which algorithms, inspired by the human brain, encourage the computer to continue recognizing patterns automatically (Figure 1). A further subset is deep learning in which massive amounts of neuronal networks interpret and use large amounts of data for deeper “cognitive” capabilities. It has also been called a convolutional neural network (CNN) in part due to its resemblance to the neurons and connections in our cerebral cortexes. Deep learning has led to breakthroughs in healthcare, specifically in radiologic image recognition.1
Use of AI in medical imaging
One of the most common uses of AI in healthcare is computer-aided diagnosis (CAD) which has already been widely studied in many fields including prostate, breast and cardiac imaging.2-4 Many AI applications are used to develop and implement protocols, thereby shortening imaging time, optimizing staffing, and reducing costs.5 They also have become instrumental in helping physicians make decisions about patient care.6 Ob/gyn, while late to the game, given the ubiquitous involvement of ultrasound in care of nearly every reproductive-aged woman in the modern world, has the potential to climb the ranks as the specialty most instrumental to use and development of AI.
The authors report no potential conflicts of interest with regard to this article.
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