4 pics 1 word daily challenge may 31 2017

The DL approach was developed to improve on the performance of conventional ANN when using deep architectures. There are three different kinds of layers: the input layer, which receives input data the output layer, which produces the results of data processing and the hidden layer(s), which extracts the patterns within the data. Weights are dynamically optimised during the training phase. Each node of the network performs a weighted sum of the input data that are subsequently passed to an activation function. Neural network architecture is structured in layers composed of interconnected nodes. ML incorporates computational models and algorithms that imitate the architecture of the biological neural networks in the brain, i.e., artificial neural networks (ANNs). The higher efficiency provided by AI will allow radiologists to perform more value-added tasks, becoming more visible to patients and playing a vital role in multidisciplinary clinical teams. Yet, they will not be replaced because radiology includes communication of diagnosis, consideration of patient’s values and preferences, medical judgment, quality assurance, education, policy-making, and interventional procedures. Radiologists, who were on the forefront of the digital era in medicine, can guide the introduction of AI into healthcare. With an irreversible increase in the amount of data and the possibility to use AI to identify findings either detectable or not by the human eye, radiology is now moving from a subjective perceptual skill to a more objective science. Neuroradiology appears in about one-third of the papers, followed by musculoskeletal, cardiovascular, breast, urogenital, lung/thorax, and abdomen, each representing 6–9% of articles. Magnetic resonance imaging and computed tomography collectively account for more than 50% of current articles. Publications on AI have drastically increased from about 100–150 per year in 2007–2008 to 700–800 per year in 2016–2017.

This article provides basic definitions of terms such as “machine/deep learning” and analyses the integration of AI into radiology. One of the most promising areas of health innovation is the application of artificial intelligence (AI), primarily in medical imaging.

4 pics 1 word daily challenge may 31 2017