A new paper from Stanford University reveals how artificial intelligence algorithms can be quickly trained to diagnose pneumonia better than a radiologist. “Using 100,000 x-ray images released by the National Institutes of Health on Sept. 27, the research published Nov. 14 (without peer review) on the website ArXiv claims its AI can detect pneumonia from x-rays with similar accuracy to four trained radiologists,” reports Quartz. From the report: That’s not all — the AI was trained to analyze x-rays for 14 diseases NIH included in the dataset, including fibrosis, hernias, and cell masses. The AI’s results for each of the 14 diseases had fewer false positives and false negatives than the benchmark research from the NIH team that was released with the data. The paper includes Google Brain founder Andrew Ng as a co-author, who also served as chief scientist at Baidu and recently founded Deeplearning.ai. He’s often been publicly bullish on AI’s use in healthcare. These algorithms will undoubtedly get better — accuracy on the ImageNet challenge rose from 75% to 95% in just five years — but this research shows the speed at which these systems are built is increasing as well.

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Source: Slashdot – Stanford Trains AI To Diagnose Pneumonia Better Than a Radiologist In Just Two Months