AI Is Close to Giving Us the Ultimate Early Diagnostic Test For Breast Cancer

By HUGH HARVEY, MD 1986 was a great year. In the heyday of the worst-dressed decade in history, the Russians launched the Mir Space Station, Pixar was founded, Microsoft went public, the first 3D printer was sold, and Matt Groening created The Simpsons. Meanwhile, two equally important but entirely different scientific leaps occurred in completely separate academic fields on opposite sides of the planet. Now, thirty two years later, the birth of deep learning and the first implementation of breast screening are finally converging to create what could be the ultimate early diagnostic test for the most common cancer in women. A brief history of deep learning 1986: In America, a small group of perceived agitators in the early field of machine learning published a paper in Nature entitled “Learning representations by back-propagating errors”. The authors, Rumelhart, Hinton and Williams had gone against the grain of conventional wisdom and proved that by re-running a neural network’s output errors backwards through a system, they could dramatically improve performance at image perception tasks. Back-propagation (or back-prop for short) wasn’t their discovery (for we all stand on the shoulders of giants) but with the publishing of this paper they managed to finally convince the sceptical machine learning community that using hand-engineering features to ‘teach’ a computer what to look for was not the way forward. Both the massive efficiency gains of the technique,...
Source: The Health Care Blog - Category: Consumer Health News Authors: Tags: Uncategorized Source Type: blogs