Research by neuroscientists at the University of Chicago shows how short-term, working memory uses networks of neurons differently depending on the complexity of the task at hand.
Harvard Medical School’s Media Fellowship program, now entering its 22nd year, is accepting applications for Fall 2019.
Below are summaries of recent Fred Hutch research, with links for additional background and media contacts.
Researchers at Columbia Engineering have developed a new technique based on reinforcement learning that trains a neural network model to correctly select the “best” reaction at each step of the retrosynthetic process. This form of AI provides a framework for researchers to design chemical syntheses that optimize user specified objectives such synthesis cost, safety, and sustainability. The new approach is more successful (by ~60%) than existing strategies for solving this challenging search problem.
Imagine for just a moment that your kettle could speak? What would it say? How would it feel? More importantly, what on earth would you ask it?
Sixty years ago, famous American economist Leonid Hurwicz did groundbreaking research about the economic mechanisms theory. Today, Darden expert is interested in designing mechanisms to solve big challenges like energy usage and traffic flows.
A tsunami of technology is about to change the way people live and work. In this introduction of the article collection Human Excellence in the Smart Machine Age, Professor Ed Hess explains what skills humans need to hone in order to meet the challenges of the near future.
Argonne researchers are transforming America's transportation and energy systems with machine learning, an iterative version of artificial intelligence.
The overpumping of groundwater in California has led to near environmental catastrophe in some areas – land is sinking, seawater is intruding, and groundwater storage capacity has shrunk. But researchers at Lawrence Berkeley National Laboratory believe machine learning could be part of the solution to restoring groundwater to sustainable levels and quality.
A team from Cornell University associate professor Max Zhang’s lab will work with the Environmental Protection Agency (EPA) over the next year on a machine learning model designed to predict fossil fuel emissions. The project was a winning entry in the EPA-sponsored EmPOWER Air Data Challenge.
A telebriefing will announce the development by the Johns Hopkins Kimmel Cancer Center of a new “liquid biopsy” to accurately detect the presence of seven cancers using machine learning, a type of artificial intelligence. The briefing will coincide with the publication of a study in the journal Nature.
Scientists have long sorted cells into different varieties based on their appearance under a microscope or, for differences that are more visually subtle, based on the behavior of a handful of genes. But in a bid to reveal even more distinctive differences and similarities, researchers from the Johns Hopkins Kimmel Cancer Center, the Johns Hopkins Institute for Genetic Medicine and the Johns Hopkins Department of Neuroscience developed two new artificial intelligence methods that decipher complex gene activity controlling cell fate decisions in retina development and relate this gene activity to what occurs in other tissues and across different species.
TU Delft scientists have created the world’s smallest autonomous racing drone. The main challenge in creating the drone lies in the use of only a single, small camera and in the highly restricted amount of processing. The main innovation is the design of robust, yet extremely efficient algorithms for motion prediction and computer vision.
Today, the Journal of the American College of Radiology (JACR®) published a report detailing real-world artificial intelligence (AI) challenges and summarizing the priorities for translational research in AI for medical imaging to help accelerate the safe and effective use of AI in clinical practice.
A new report, with contributions from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), part of the National Institutes of Health, provides a roadmap for translational research on artificial intelligence (AI) in medical imaging. The report, published in the May 28, 2019, Journal of the American College of Radiology.
In a new study from the U.S. Department of Energy’s (DOE) Argonne National Laboratory, researchers used the power of artificial intelligence and high-performance supercomputers to introduce and assess the impact of different configurations of defects on the performance of a superconductor.
In this episode, a look at preparing for the future in two very different economic circumstances: In the US, how AI and advanced technology could disrupt the workforce; in the Amazon basin, how indigenous people are bolstering production of a common food staple.
Using machine learning to analyze jaw movements during sleep, doctors may be able to diagnose obstructive sleep apnea in patients with mild to severe OSA with an accuracy comparable to polysomnography, the gold standard for OSA diagnosis,
The University of Pittsburgh School of Medicine and Carnegie Mellon University have each been awarded 4-year contracts totaling nearly $7.5 million from the U.S. Department of Defense to create an autonomous trauma care system that fits in a backpack and can treat and stabilize soldiers injured in
Results of a pilot study conducted by researchers from the National University of Singapore provided evidence that an artificial intelligence known as CURATE.AI has the potential to enhance learning, and could pave the way for promising applications in personalised digital therapy, including the prevention of cognitive decline.
A team of engineers from the National University of Singapore has designed a set of novel noise attenuating blocks that targets low frequency noise.
Feature introduces video of interview with physicist William Tang describing the role of artificial of intelligence in fusion research. Feature includes a link to the video
Engineers at Rensselaer Polytechnic Institute are working to improve imaging methods in order to make medicine more precise and personalized. This work will be a critical component of a new interdisciplinary research project funded with $1.4 million from the National Institutes of Health (NIH) that seeks to improve radiation therapy for high-risk prostate cancer patients.
Release describes application of machine learning form of artificial intelligence to predict the behavior of fusion plasma.
Researchers in the Penn State Department of Mechanical Engineering recently received a $389,919 grant from the National Science Foundation (NSF) to investigate, explore and innovate new flying mechanisms for micro air vehicles (MAVs) to better mimic the performance and agility of flying animals.
A Berkeley Lab-led research group is using a deep learning method known as generative adversarial networks to enhance the use of gravitational lensing in the study of dark matter.
“Penn AI” is now accessible to anyone from high school students to biomedical researchers, on any computer or laptop
Researchers at UC Davis Health and UC San Francisco have found a way to teach a computer to detect one of the hallmarks of Alzheimer’s disease
Researchers at the UW have created a new smartphone app that can detect fluid behind the eardrum by simply using a piece of paper and the phone’s microphone and speaker.
Researchers at UC Davis and UC San Francisco have found a way to teach a computer to precisely detect one of the hallmarks of Alzheimer’s disease in human brain tissue, delivering a proof of concept for a machine-learning approach to distinguishing critical markers of the disease.
Using data from eBay, which managed more than $14 billion in trade across more than 200 countries in 2014, two Washington University in St. Louis researchers demonstrated that a moderate improvement in the quality of language translation increased trade between countries on eBay 10.9%.
The conference will convene thought leaders from the private sector, international NGOs, foundations, academia and local, state and federal governments to delve into topics such as smart cities and urban innovation.
Oregon State University roboticist Heather Knight programs her robots with artificial social intelligence to help them interpret and mimic human cues — like body language, gaze direction, movement patterns, and facial expressions — to make them more effective at collaborating with humans.
Today, Stony Brook University officially launched the new Institute for AI-Driven Discovery and Innovation to advance AI research and apply the transformative power of innovation driven by AI across disciplines. The AI Institute will focus on four grand challenges: health care; infrastructure; education; and, finance. It will also focus on five foundational research areas: automated and scalable knowledge acquisition; predictive intelligence; explainable AI; trustworthy AI; and, ethical AI.
Your friendly neighborhood hummingbirds. If drones had this combo, they would be able to maneuver better through collapsed buildings and other cluttered spaces to find trapped victims.
To help non-professionals create visual blends for their news and PSAs, Columbia Engineering researchers have developed VisiBlends, a flexible, user-friendly platform that transforms the creative brainstorming activity into a search function, and enables a statistically higher output of visually blended images. The VisiBlends platform combines a series of human steps or “microtasks” with AI and computational techniques. Crowd-sourcing is a key component of the system enabling groups of people to collaborate, either together or off-site.
Saint Louis University researchers paired satellite imaging data with machine learning techniques to map local tree species and health.
A machine learning algorithm can detect signs of anxiety and depression in the speech patterns of young children, potentially providing a fast and easy way of diagnosing conditions that are difficult to spot and often overlooked in young people. If undiagnosed, they can lead to an increased risk of substance abuse and suicide later in life.
Provides priority regulatory review of AI-enabled diagnostic for fast-progressing kidney disease
Precision agriculture engineer Yiannis Ampatzidis sees a day when citrus farmers use artificial intelligence to detect the pin-sized insects that can infect the fruit’s trees with the deadly greening disease. That day could come in the near future, because Ampatzidis and his research team are starting to perfect a system to detect the potentially deadly Asian citrus psyllid.
A team of Texas State University researchers including; Dr. Damian Valles, assistant professor at the Ingram School of Engineering; Dr. Maria Resendiz, associate professor for the College of Health Professions; and graduate student MD Inzamam Haque, is developing a mobile application to help children with ASD recognize facial expressions on a device screen allowing children to better interpret nonverbal ques in social settings.
Ablacon, Inc. (www.ablacon.com), a Wheat Ridge, CO-based company developing an advanced mapping system to guide the treatment of atrial fibrillation (AFib)
With so much at stake, should Airbnb hosts rely on an algorithm to write their profiles for them? That depends, according to new research from Cornell and Stanford University. If everyone uses algorithmically generated profiles, users trust them. However, if only some hosts choose to delegate writing responsibilities to artificial intelligence, they are likely to be distrusted.
Many artificial intelligence ideas for healthcare are far-fetched or still years away from touching patients. However, the stroke service line at LifeBridge Health has been using “AI” at the beside since late 2016, and it’s already helping physicians save lives.
Researchers have discovered a simple, cost-effective, and accurate new method for equipping self-driving cars with the tools needed to perceive 3D objects in their path.
Sandia announced today the formation of Autonomy New Mexico, a national academic research coalition whose mission is to create artificially intelligent aerospace systems.
Today, the U.S. Department of Energy (DOE) announced a total of $20 million in funding for innovative research and development in artificial intelligence (A.I.) and machine learning.
This week, the first of two reports establishing a research roadmap outlining priorities in foundational and translational research in artificial intelligence for medical imaging was published in the journal Radiology. It will be closely followed by a second report on translational research in AI to be published in the Journal of the American College of Radiology (JACR) in early summer focusing on real-world AI problems.
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