Natural language processing (NLP) is a family of techniques that often use machine learning to analyze, process, and generate natural language text. It enables computers to process human language and derive meaning from natural language. For example, NLP-driven software can translate text from one language to another. It is also used by search engines to enhance the search experience by suggesting commonly used search terms and subsequent words in common phrases. Techniques that use NLP have also found applications in radiology, enabling the automatic identification and extraction of information from radiologists’ reports.
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Machine Learning
Improving Blood Pressure Measurements Using Machine Learning
Blood pressure diseases have increasingly been identified as being among the main factors threatening human health.¹ Measuring and monitoring blood pressure regularly is important for the early detection and diagnosis of diseases related to blood pressure and to ensure timely treatment and prevention. Medical devices using algorithms enhanced by machine learning can improve blood pressure measurements. Such devices are the subject of active research at the intersection between health care and machine learning.
Kyle Mills’s Journey from Ph.D. Student to Being on the Cover of Nature Machine Intelligence
1QBit scientist Kyle Mills’s research was recently featured in the September issue of Nature Machine Intelligence. The research discovered new ways to use reinforcement learning to find the ground states of spin Hamiltonians. Kyle worked with Pooya Ronagh, Head of the Hardware Innovation Lab at 1QBit, and Isaac Tamblyn from the National Research Council of Canada.