Deep Learning
Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence. See these course notes for a brief introduction to Machine Learning for AI and an introduction to Deep Learning algorithms. Deep Learning is about learning multiple levels of representation and abstraction that help to make sense of data such as images, sound, and text. [1]
Deep Learning is an emerging topic in data analysis. Deep Networks are special kinds of neural networks that try to mimic biological neural networks in hardware or software. Though neural networks is a very old topic in computer science, in recent years surprising advances have been made in this area. This is evidenced by several awards in very diverse learning competitions including speech, handwriting recognition, speech translation, vision, and game playing. Some of these advances are due to better learning algorithms and/or very clever network architectures, others are simply due to much better, highly parallel hardware. More recently, companies like Google and Facebook have started making major investments in the area of deep learning, e.g. in 2014, Google acquired Deep Mind for approximately 500 million pounds; Facebook founded a deep learning lab in Paris. In addition, some of the fascinating results of deep learning created big waves in the press, e.g. Google Inceptionism and Google Deep Dream.
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Ultrasound imaging - The company Samsung Medison applied deep learning technology to ultrasound imaging in breast lesion analysis. Their ultrasound device for breasts utilizes big data collected from numerous breast exam cases and provides the characteristics of the displayed lesion as well as a recommendation on whether the selected lesion is benign or malignant. Deep learning algorithm applied in the lesion segmentation, characteristic analysis, and assessment processes gives more accurate results which can reduce the number of unnecessary biopsies and provide more reliable support in accurately detecting malignant and suspicious lesions. [2]
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