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Research and identify an article or blog post that details a complicated real-world problem that was solved (or remains unsolved) using data analytics or predictive analytics.

Include details about the problem space itself, the technologies that were used to solve the problem, and what difficulties they encountered. If the problem remains unsolved be sure to mention why and the obstacles that haven't been overcome.

I chose an artical on Healthcare, specifically using Data Science and machine learning technologies to aid doctors in predicting potential diseases before it become more severe. This is a story of success, Googles LYmph Node Assistant (LYNA) has shown great results in detection of breast cancer. The LYmph Node Assistant was incredibly successful in both datasets, correctly distinguishing slides with metastatic cancer from those without cancer 99% of the time. It could even identify areas of concern within each slide that was too small to be detected by pathologists. This could help them greatly, as LYNA could highlight these areas of concern for pathologists to review and make the final diagnosis faster than ever. LYNA was applied to pathology slides from the Camelyon Challenge and an independent dataset provided by the Naval Medical Center San Diego. This additional dataset improved the representation of the diversity of slides and artifacts seen in routine clinical trials. Such an impressive use of our technology!