Seizure forecasting with wrist-worn devices possible for people with epilepsy, study shows

Despite medications, surgery and neurostimulation devices, many people with epilepsy continue to have seizures. The unpredictable nature of seizures is severely limiting. If seizures could be reliably forecast, people with epilepsy could alter their activities, take a fast-acting medication or turn up their neurostimulator to prevent a seizure or minimize its effects.

A new study in Scientific Reports by Mayo Clinic researchers and international collaborators found patterns could be identified in patients who wear a special wristwatch monitoring device for six to 12 months, allowing about 30 minutes of warning before a seizure occurred. This worked well most of the time for five of six patients studied.

Want to throw off your chatbot? Use figurative language

Computer scientists recently examined the performance of dialog systems, such as personal assistants and chatbots designed to interact with humans. The team found that when these systems are confronted with dialog that includes idioms or similes, their performance drops to between 10 and 20 percent. The research team also developed a partial remedy.

Engineering Researchers Receive $1 Million NSF Grant for First Networked-AI Testbed

Just like humans, autonomous robots need to communicate with one another to learn together and to accomplish a team mission such as search and rescue. Researchers are developing the nation’s first-of-its-kind testbed platform that connects robots using high-frequency radio waves (30 to 300 gigahertz). The robots will be able communicate at ultra-high speeds of gigabits per second by forming and directing ‘beams’ toward each other that also will enable them to see through objects as needed. They will see what the other robots are sensing in real-time, resulting in five times the eyes thanks to the nearly instantaneous exchange of high volumes of data.

Data Scientist Discusses Job Outlook in Era of Artificial Intelligence

Recent worker shortages and higher labor costs have resulted in more automated jobs, including service and professional jobs economists once considered safe. Predictions are mixed on job losses going forward, although the World Economic Forum (WEF) concluded in a 2020 report that “a new generation of smart machines, fueled by rapid advances in artificial intelligence and robotics, could potentially replace a large proportion of existing human jobs.”

Joaquin Carbonara, Buffalo State College professor of mathematics, weighed in on AI’s effect on the job market now and in the future.

Novel Tag Provides First Detailed Look into Goliath Grouper Behavior

A study is the first to reveal detailed behavior of massive goliath groupers. Until now, no studies have documented their fine-scale behavior. What is known about them has been learned from divers, underwater video footage, and observing them in captivity. Using a multi-sensor tag with a three axis accelerometer, gyroscope and magnetometer as well as a temperature, pressure and light sensor, a video camera and a hydrophone, researchers show how this species navigates through complex artificial reef environments, maintain themselves in high current areas, and how much time they spend in different cracks and crevices – none of which would be possible without the tag.

Key to resilient energy-efficient AI/machine learning may reside in human brain

A clearer understanding of how a type of brain cell known as astrocytes function and can be emulated in the physics of hardware devices, may result in artificial intelligence (AI) and machine learning that autonomously self-repairs and consumes much less energy than the technologies currently do, according to a team of Penn State researchers.

All About Eve

New AI model called EVE, developed by scientists at Harvard Medical School and Oxford University, outperforms other AI methods in determining whether a gene variant is benign or disease-causing.
When applied to more than 36 million variants across 3,219 disease-associated proteins and genes, EVE indicated more than 256,000 human gene variants of unknown significance that should be reclassified as benign or pathogenic.

AI Tool Pairs Protein Pathways with Clinical Side Effects, Patient Comorbidities to Suggest Targeted Covid-19 Treatments

Researchers led by Jeffrey Skolnick have designed a new AI-based “decision prioritization tool” that combines data on protein pathways with common Covid-19 side effects and known patient comorbidities. The tool offers possible targeted treatment options with existing FDA-approved drugs to foster better health outcomes for individuals fighting Covid-19.

LLNL joins Human Vaccines Project to accelerate vaccine development and understanding of immune response

Lawrence Livermore National Laboratory has joined the international Human Vaccines Project, bringing Lab expertise and computing resources to the consortium to aid development of a universal coronavirus vaccine and improve understanding of immune response.

AI-driven dynamic face mask adapts to exercise, pollution levels

Researchers reporting in ACS Nano have developed a dynamic respirator that modulates its pore size in response to changing conditions, such as exercise or air pollution levels, allowing the wearer to breathe easier when the highest levels of filtration are not required.

Researchers predict viewer interest, not just attention, in public screen content

We are constantly surrounded by screens that offer us information on the weather, current events or the latest offers from the corner shop. Yet most displays are updated manually, if at all. Researchers at Aalto University and the Finnish Center for Artificial Intelligence FCAI have developed a new, simpler way to choose and arrange public display content so that it really catches people’s attention.

Novel Insights on COVID-19 Vaccines and Virus Evolution, Artificial Intelligence in the Clinic, Miniaturization of Diagnostic Platforms, and Much More to Be Explored at the 2021 AACC Annual Scientific Meeting & Clinical Lab Expo

At the 2021 AACC Annual Scientific Meeting & Clinical Lab Expo, laboratory medicine experts will present the cutting-edge research and technology that is revolutionizing clinical testing and patient care.

Preparing for exascale: Argonne’s Aurora supercomputer to drive brain map construction

Argonne researchers are mapping the complex tangle of the brain’s connections — a connectome — by developing applications that will find their stride in the advent of exascale computing.

New machine learning method to analyze complex scientific data of proteins

Scientists have developed a method using machine learning to better analyze data from a powerful scientific tool: nuclear magnetic resonance (NMR). One way NMR data can be used is to understand proteins and chemical reactions in the human body. NMR is closely related to magnetic resonance imaging (MRI) for medical diagnosis.

Department of Energy Invests $1 Million in Artificial Intelligence Research for Privacy-Sensitive Datasets

The U.S. Department of Energy (DOE) announced $1 million for a one-year collaborative research project to develop artificial intelligence (AI) and machine learning (ML) algorithms for biomedical, personal healthcare, or other privacy-sensitive datasets.

Peachy Robot: A Glimpse into the Peach Orchard of the Future

Researchers are developing a robot that utilizes deep learning to automate certain aspects of the peach cultivation process, which could be a boon for many Georgia peach farms grappling with a shortage of workers. The self-navigating robot uses an embedded 3D camera to determine which trees need to be pruned or thinned, and removes the branches or peaches using a claw-like device attached to its arm.

Department of Energy Invests $16 Million in Data-Intensive Scientific Machine Learning Research and Analysis

The U.S. Department of Energy (DOE) announced $16 million for five collaborative research projects to develop artificial intelligence (AI) and machine learning (ML) algorithms for enabling scientific insights and discoveries from data generated by computational simulations, experiments, and observations.

‘Molecular Twin’ Initiative Will Help Advance Precision Cancer Treatment

Cedars-Sinai Cancer and Tempus, a leader in artificial intelligence and precision medicine, are harnessing the power of big data and AI to design personalized cancer treatment options by creating virtual replicas of patients’ DNA, RNA, protein and other information to help identify the most effective approach to each individual’s disease.

Unbound Medicine Launches Upgrade to Study System Using Artificial Intelligence

Unbound Medicine announced an upgrade to Grasp, their personal mobile study system. This latest version utilizes Unbound Intelligence, exclusive artificial intelligence and machine learning tools developed to help clinicians discover and fill knowledge gaps, as well as keep up to date with research.

Do Passengers Want Self-driving Cars to Behave More or Less Like Them?

Researchers asked participants about their personal driving behaviors such as speed, changing lanes, accelerating and decelerating and passing other vehicles. They also asked them the same questions about their expectations of a self-driving car performing these very same tasks. The objective of the study was to examine trust and distrust to see if there is a relationship between an individual’s driving behaviors and how they expect a self-driving car to behave.

U.S. Department of Energy’s Argonne National Laboratory and Hewlett Packard Enterprise prepare for exascale era with new testbed supercomputer

Argonne and HPE unveiled a new testbed supercomputer that will enable scientists and developers to test and optimize software codes and applications for the forthcoming exascale supercomputer, Aurora.

Baby detector software embedded in digital camera rivals ECG

Facial recognition is now common in adults, but University of South Australia researchers have developed software that can reliably detect a premature baby’s face in an incubator and remotely monitor its heart and breathing rates, rivalling ECG machines and even outperforming them. This is the first step in using non-contact monitoring in neonatal wards, avoiding skin tearing and potential infections from adhesive pads.x

Artificial Intelligence aids in discovery of new prognostic biomarkers for breast cancer

Scientists at Case Western Reserve University have used Artificial Intelligence (AI) to identify new biomarkers for breast cancer that can predict whether the cancer will return after treatment—and which can be identified from routinely acquired tissue biopsy samples of early-stage breast cancer.