Background: The mitotic count in breast carcinoma is an important prognostic marker. Unfortunately substantial inter- and intra-laboratory variation exists when pathologists manually count mitotic figures. Artificial intelligence (AI) coupled with whole slide imaging offers a potential solution to this problem. The aim of this study was to accordingly critique an AI tool developed to quantify mitotic figures in whole slide images of invasive breast ductal carcinoma.
Today, Amazon Web Services (AWS) launched Amazon Rekognition Custom Labels, a new feature of Amazon Rekognition that enables customers to build their own machine learning (ML) based image analysis capabilities to detect unique objects and scenes, relevant to their business need. For example, customers using Amazon Rekognition to detect machine parts from images can now train a ML model with a small set of labeled images to detect "turbochargers" and "torque converters" without needing any ML expertise. Instead of having to train a model from scratch, which requires specialized machine learning expertise and millions of high-quality labeled images, customers can now use Amazon Rekognition Custom Labels to achieve state-of-the-art performance for their unique image analysis needs.
Although the genome is generally thought to be transcriptionally silent during mitosis, technical limitations have prevented sensitive mapping of transcription during mitosis and mitotic exit. Thus, the means by which the interphase expression pattern is transduced to daughter cells have been unclear. We used 5-ethynyluridine to pulse-label transcripts during mitosis and mitotic exit and found that many genes exhibit transcription during mitosis, as confirmed with fluorescein isothiocyanate–uridine 5′-triphosphate labeling, RNA fluorescence in situ hybridization, and quantitative reverse transcription polymerase chain reaction. The first round of transcription immediately after mitosis primarily activates genes involved in the growth and rebuilding of daughter cells, rather than cell type–specific functions. We propose that the cell's transcription pattern is largely retained at a low level through mitosis, whereas the amplitude of transcription observed in interphase is reestablished during mitotic exit.
You know how old you are. You know how old your friends think you are. Heck, you even know how old Microsoft thinks you are. But at the end of the day, does anyone other than Amazon really matter? Until now, the only way for you to know how old Amazon thought you were was to look at products recommended to you.
Amazon hasn't exactly kept Rekognition under wraps. In late 2016, the software giant talked up its facial detection software in a relatively benign AWS post announcing that the tech was already being implemented by The Washington County Sheriff's Office in Oregon for suspect identification. The ACLU of Northern California is shining more light on the tech this week, however, after announcing that it had obtained documents shedding more light on the service it believes "raises profound civil liberties and civil rights concerns." The documents in question highlight Washington County's database of 300,000 mug shot photos and a mobile app designed specifically for deputies to cross-reference faces. They also note that Amazon has solicited the country to reach out to other potential customers for the service, including a company that makes body cameras.