首页|Food and Drug Administration Reports Findings in Machine Learning (Exploring syn thetic datasets for computer-aided detection: a case study using phantom scan da ta for enhanced lung nodule false positive reduction)
Food and Drug Administration Reports Findings in Machine Learning (Exploring syn thetic datasets for computer-aided detection: a case study using phantom scan da ta for enhanced lung nodule false positive reduction)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting out of Silver Spring, Marylan d, by NewsRx editors, research stated, “Synthetic datasets hold thepotential to offer cost-effective alternatives to clinical data, ensuring privacy protection s and potentiallyaddressing biases in clinical data. We present a method levera ging such datasets to train a machinelearning algorithm applied as part of a co mputer-aided detection (CADe) system.”
Silver SpringMarylandUnited StatesNorth and Central AmericaComputersCyborgsEmerging TechnologiesMachine Le arningU.S. Food and Drug Administration
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