The Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) is a collaboration between McGill University and Forschungszentrum Jülich to develop next-generation high-resolution human brain models using cutting-edge Machine- and Deep Learning methods and high-performance computing. HIBALL is based on the high-resolution BigBrain model first published by the Jülich and McGill teams in 2013. Over the next five years, the lab will be funded with a total of up to 6 million Euro by the German Helmholtz Association, Forschungszentrum Jülich, and Healthy Brains, Healthy Lives at McGill University. In 2003, when Jülich neuroscientist Katrin Amunts and her Canadian colleague Alan Evans began scanning 7,404 histological sections of a human brain, it was completely unclear whether it would ever be possible to reconstruct this brain on the computer in three dimensions. At that time, there were no technical possibilities to cope with the huge amount of data.
Imagine a dressing that releases antibiotics on demand and absorbs excessive wound exudate at the same time. Researchers at Eindhoven University of Technology hope to achieve just that, by developing a smart coating that actively releases and absorbs multiple fluids, triggered by a radio signal. This material is not only beneficial for the health care industry, it is also very promising in the field of robotics or even virtual reality. TU/e-researcher Danqing Liu, the lead author of this paper, and her Ph.D. student Yuanyuan Zhan are inspired by the skins of living creatures. Human skin secretes oil to defend against bacteria and sweats to regulate the body temperature.
Nowadays it's hard to find a single industry where machine learning and data science aren't being used to improve productivity and deliver results. Indeed that is why people are so excited about the promise of artificial intelligence: it can be applied to so many diverse problem spaces effectively and it works! This list has been aggregated after analyzing over 200 company descriptions, and we've broadly organized them by the problem domain being tackled and have included a brief description of their mission. TLDR: A framework for providing data integrations and web interfaces for trained machine learning models. TLDR: Develops medical imaging tools powered by AI to help improve the efficacy of radiologists in detecting illnesses.
The device that allows the human brain to connect to a computer could be implanted in a person for the first time later this year, announced the founder of Neuralink neurotechnology company, the tycoon Elon Musk. Last year, Musk's Neuralink introduced a special microchip and flexible fiber electrodes that should allow the human brain to connect to computers or machines. At the same time, he announced that the electrodes in question would like to be implanted with a laser in the future because it is more suitable than a mechanical drill for making holes in the skull. This crazy project of Elon Musk and his startup seems to be going well. Elon Musk said on Twitter that the Neuralink is working on an "awesome" new version of the company's signature device.
One kind of robot has endured for the last half-century: the hulking one-armed Goliaths that dominate industrial assembly lines. These industrial robots have been task-specific -- built to spot weld, say, or add threads to the end of a pipe. They aren't sexy, but in the latter half of the 20th century they transformed industrial manufacturing and, with it, the low- and medium-skilled labor landscape in much of the US, Asia, and Europe. You've probably been hearing a lot more about robots and robotics over the last couple years. That's because, for the first time since the 1961 debut of GM's Unimate, regarded as the first industrial robot, the field is once again transforming world economies. Only this time the impact is going to be broader. That's particularly true in light of the COVID-19 pandemic, which has helped advance automation adoption across a variety of industries as manufacturers, fulfillment centers, retail, and restaurants seek to create durable, hygienic operations that can withstand evolving disruptions and regulations.
Are you looking for the Best R Programming Certification Online? Here is the handpicked list of Best R Programming Course & Training to assist you to become an expert in programming in R. Before you start doing these courses we have included an article How to Start Programming in R? Go through this article you will get a brief idea about where and how to start learning r? Find out how attractive the r programming jobs are? Description: Learn R will help you gain expertise in R Programming, Data Manipulation, Exploratory Data Analysis, Data Visualization, Data Mining, Regression, Sentiment Analysis and using R Studio for real-life case studies on Retail, Social Media. "R" wins on Statistical Capability, Graphical capability, Cost, a rich set of packages and is the most preferred tool for Data Scientists. Description: Neurohacking describes how to use the R programming language and its associated package to perform manipulation, processing, and analysis of neuroimaging data.
Hoy traemos a este espacio el último número, el Vol 16, No 02 (2020) del International Journal of Online and Biomedical Engineering (iJOE) The objective of the journal is to publish and discuss fundamentals, applications and experiences in the field of remote engineering, cyber-physical systems, virtual instrumentation and online simulations. The use of virtual and remote controlled devices and remote laboratories is one of the future trend developments for advanced teleworking/e-working environments. Online Engineering is the future trend in engineering and science. It covers working directions such as remote engineering, cyber-physical systems, virtual instrumentation, simulation techniques and others. Readers don't have to pay any fee.
Clinical voice assistant developer Suki has created a new voice platform with improved artificial intelligence. The Suki Speech Service, referred to by the company as S3, makes Suki's voice assistant faster, more accurate, and flexible enough that it could be used by professionals outside of the healthcare sector. Suki's current voice assistant is built to reduce the amount of time and energy doctors spend on administrative tasks and records. The voice assistant records, transcribes, and organizes a doctor's conversations with a patients and any notes on the case. Suki can then automatically complete the data entry necessary for Electronic Health Records (EHR).
Much proselytizing has occurred regarding the value and future of artificial intelligence (AI) and machine learning in healthcare. As with blockchain technology, which continues to evolve in the healthcare marketplace, AI and machine learning are constructs that require a bit of near-term expectation management. While their efficacy and value will improve with time, they are not the magic bullet (at present) that will answer the myriad care and cost delivery questions surrounding healthcare in the United States. Owing to space constraints this column is an overly simplistic contemplation of AI. As prologue to this article, I am not an AI programmer, don't play in Python, and have never built a machine learning algorithm.