Articles tagged with Artificial Intelligence
Researchers developed a new AI algorithm called 'basis profile curve identification' to simplify comparisons between effects of electrical stimulation on the brain. The algorithm may help understand which brain regions interact with each other, guiding placement of electrodes for treating network brain diseases.
A new algorithm, Phe2vec, accurately identified patients with certain diseases, outperforming traditional methods in classifying diagnoses. The study suggests that this automation will facilitate further research in clinical informatics.
Researchers at Technical University of Munich have developed a new machine learning algorithm that can analyze complex markets and their equilibrium strategies. This breakthrough has potential applications in auction theory, wireless spectrum auctions, and more.
A review of 23 studies found AI systems were less accurate than humans and radiologists in detecting breast cancer. The quality of methods used was poor, and the applicability to European or UK breast cancer screening programmes was low.
Researchers developed an AI tool that can quickly and accurately identify suspicious proteins in the body by analyzing their movements. The method, known as diffusional fingerprinting, uses machine learning algorithms to predict protein behavior with over 90% accuracy.
A study found that Airbnb's Smart Pricing algorithm narrowed the racial revenue gap, but only for Black hosts who adopted it. The algorithm increased monthly occupancy and overall revenue for Black hosts by nearly 9% and $13.92 a night.
A new research project, FLOCKD, will allow smart digital units to autonomously share information with nearby units, enabling faster learning and more intelligent system behavior. The goal is to achieve synergetic problem-solving and improve overall performance.
Researchers developed a model to predict the risk of death and unplanned cardiac hospitalization among patients awaiting cardiac surgery. The tool, based on an ethnically diverse group of 62,375 patients, identifies factors such as gender, urban residency, and cardiac symptoms that increase the risk of adverse events.
Researchers developed scArches to compare single-cell genomics data with existing references, enabling accurate diagnosis of diseases like COVID-19. The algorithm uses transfer learning to preserve privacy and democratize the usage of single-cell reference atlases.
Scientists created a reliable true random number generator using atomically thin two-dimensional films, overcoming long-term stability issues and power consumption concerns. The innovation uses memristors to produce fluctuating electronic signals with an exceptionally high degree of randomness.
A new AI tool called IceNet has been developed to predict Arctic sea ice conditions with high accuracy. The system is almost 95% accurate in forecasting sea ice presence two months ahead, addressing the challenge of predicting Arctic sea ice forecasts for decades.
Researchers at UCLA have developed a computational technique powered by artificial intelligence that transforms images of tissue previously stained with H&E into new ones with added special stains. The process takes less than one minute per tissue sample, significantly improving diagnoses in medical conditions such as organ transpl...
Student researchers at the University of Cincinnati developed artificial intelligence to train robots to work together to move a couch around obstacles and through a narrow door. The robots successfully completed the task 95% of the time in simulations, with nearly equal success without re-training.
The robotic white cane system combines depth data with a 2D floor plan map to reduce pose estimation errors. It features a novel 'robotic roller tip' interface that allows for automatic mode-switching, making it easier for visually impaired users to navigate.
A North Carolina State University panel of experts assesses AV deployment risks and benefits, predicting substantial benefits if well-regulated. The study's findings suggest regulations could limit urban use of AVs and commercial fleet ownership, reducing risk and increasing benefits.
Drones are not the only vehicles at the forefront of automating deliveries; researchers have developed a control strategy for ships and partnered tugs to navigate environmental disturbances. The multi-layer, multi-agent control scheme increases efficiency in the shipping process while reducing human error.
Researchers from University of Notre Dame discovered that behavioral inertia can be beneficial in service center operations, particularly when agents are experts or handling difficult calls. The study suggests striking a balance between automated routing systems and agent discretion to maximize efficiency and effectiveness.
A recent study suggests that personal carbon allowances (PCAs) may be a feasible solution to reduce emissions and promote sustainable lifestyles. The researchers propose a market-based approach to provide individuals with incentives and options to link their actions with global carbon reduction goals.
Cornell University researchers used facial recognition AI to develop an imaging robot called BlackBird that scans grape leaf samples automatically, reducing manual assessment time from six months to one day. The technology has the potential to save farmers billions of dollars by detecting disease early and reducing fungicide usage.
A single-center retrospective study found that AI-CAD reduced recall rates and improved accuracy compared to digital mammography (DM) and DBT. The study showed lower recall rates and higher accuracy for DM with AI-CAD, indicating a practical addition to lowering false-positive findings.
Researchers have created an AI software that uses Minecraft to test its ability to plan for future events and solve complex tasks. The software, developed by Penn State researchers, aims to advance artificial intelligence in areas such as robotics, logistics management, and drone flight.
Researchers developed an image-based detection system using artificial intelligence models to diagnose COVID-19 from chest X-rays. The model accurately differentiated between COVID-19, pneumonia, and healthy patients, showing great promise for precision medicine.
Researchers at MIT have created an algorithm that enables drones to navigate complex obstacle courses at high speeds without crashing. The new approach combines simulations with real-world experiments, allowing drones to adapt to challenging aerodynamics and find the fastest routes.
A joint research team from POSTECH and KIMS developed a faster and more accurate microstructure imaging technique using deep learning. The technique enhanced the resolution of existing microstructure images up to 4, 8, or 16 times, reducing imaging time by up to 256x compared to conventional SEM systems.
Scientists at CiTIUS have developed a new fast support vector classifier (FSVC) that significantly improves data classification using Machine Learning techniques. The FSVC is much faster and operates with less memory than traditional approaches, making it suitable for large-scale classification problems.
Researchers have created an artificial neuron that uses ions instead of electrons for information transmission, achieving a similar energy efficiency as the human brain. The device's ion channels and clusters replicate those found in neurons, allowing for the emission of action potentials and transmission of information.
Researchers at OIST Graduate University develop robots capable of conducting complex experiments and analyzing data. The 'Nobel Turing Challenge' achieves significant advancements in scientific discovery by leveraging AI-driven robotics.
Researchers at KAIST have developed a brain-inspired highly scalable neuromorphic hardware by co-integrating single transistor neurons and synapses. This innovation dramatically reduces hardware cost and accelerates the commercialization of neuromorphic hardware, enabling its application in mobile and IoT devices.
Researchers developed an AI-powered tool to identify and recommend jobs based on underlying skill sets, increasing the chances of success in job transitions. The system can also respond to changes in job demand and provide precise skills needed to transition to a new occupation.
A team of computer scientists has developed an assembly selection process that balances representation and fairness in citizens' assemblies. By using a machine learning-based algorithm, the researchers ensure that all volunteers have an equal chance of being chosen, regardless of demographic quotas or education level.
A team of researchers found that when people use mental abstractions, the brain area that signals valuable information becomes highly active. This discovery could lead to new advances in basic research, education, rehabilitation, and artificial intelligence.
A new app called selfBACK has been developed to help people deal with back pain in a better way. The app uses artificial intelligence and draws on other people's experiences with back pain to provide tailored advice and feedback.
Researchers at UIC have received a $725,000 grant to develop an AI system that can help protect US Navy divers from waterborne bacteria, parasites, and other harmful pathogens. The system aims to provide real-time information on water conditions, allowing divers to make informed decisions about their mission.
Researchers develop hands-on labs to educate high school students about AI and cybersecurity ethics issues, aiming to increase empathy for vulnerable populations. The project uses functional near-infrared spectroscopy to assess the impact of these labs on brain regions associated with empathy.
The Institute for Learning-enabled Optimization at Scale (TILOS) will explore the interplay between artificial intelligence and optimization to develop methods that can change real-world practice. Foundational research will drive important applications in chip design, robotics, and communication networks.
The University of Washington is leading a new NSF institute focused on using artificial intelligence to understand dynamic systems, which describe chaotic situations where conditions are constantly shifting and hard to predict. The institute aims to integrate fundamental AI theory with applications in critical technological areas.
The UMass Amherst AI-EDGE institute will focus on designing wireless edge networks that are efficient, reliable, and secure. The goal is to solve long-standing distributed AI challenges by analyzing and managing vast amounts of data in real-time.
The institute will develop predictive digital twins of individual crop plants and entire farm fields, integrating real-time data from sensors to optimize crop growth. By leveraging expertise in plant sciences, engineering, and technology, AIIRA aims to accelerate agricultural productivity and sustainability.
Scientists developed new AI-based tools to identify and study materials exhibiting a metal-insulator transition (MIT), which could lead to faster and more energy-efficient microelectronic devices. The tools provide a freely available database, online classifier, and new features for characterizing these materials.
Researchers have identified a recurring trend of elevated blood glucose levels among those with severe Covid-19, which impairs lung immune defense and facilitates cytokine storm. Tight control and management of glycemia may be crucial for better outcomes, and metformin shows potential as a treatment option.
A team of scientists used hybrid machine learning methods to predict the incidence of heatstroke in Japanese cities. They achieved a high level of accuracy using publicly available information such as demographics and weather forecasts.
Researchers developed a new framework using deep learning techniques to create 3D visualizations from X-ray data. This method is hundreds of times faster than traditional methods, enabling scientists to analyze large amounts of 3D data more efficiently.
Scientists at the University of Sydney and Japan's National Institute for Material Science discover an artificial network of nanowires can be tuned to respond in a brain-like way when electrically stimulated. By keeping the network at the edge of chaos, it performs tasks at an optimal level, suggesting neural intelligence is physical.
Researchers found that clickbait headlines often performed worse than traditional headlines in attracting readers. The studies also suggest that using artificial intelligence to detect fake news by classifying headlines alone may be complicated and not effective.
New CONSORT-AI extension addresses limitations in AI study reporting, promoting standardization and improving the validity of AI studies in dentistry. With the growth of AI in clinical trials, standardized reporting is crucial to gauge methodology, bias, and replication.
Researchers developed a deep learning network using data from over 20,000 patients to predict annualized risk for heart attack or death. The network identified regions of the heart associated with high-risk patients and provided rapid risk scores.
Despite a 19% increase in global spending on science and a 13.7% rise in scientists, significant disparities remain, with only two countries accounting for nearly 63% of the investment. The report highlights the need for more diverse and inclusive science policy, emphasizing the importance of women's participation in research.
A new study found that people trust AI as much as humans, but are unwilling to compromise and cooperate with machines. Researchers conducted large-scale online studies using methods from behavioral game theory, finding a consistent pattern of 'algorithm exploitation' where humans exploit AI's benevolence for personal gain.
Scientists used drones and artificial intelligence to analyze over 10,000 images of seabirds in the Falkland Islands, achieving accurate counts with 97% accuracy for albatrosses and 87% for penguins. This technology increases ability to monitor seabird colonies worldwide and track marine ecosystem health.
Recent studies challenge the long-held assumption that variability in children's speech is solely due to developmental delays. Instead, factors such as socioeconomic status, dialects, and exposure to languages play a significant role. Experts argue that caregivers can aid in this process through conversations about different words and ...
A large majority of the Spanish population, 85%, supports increased government investment in science and technology. The survey also reveals a higher interest in science and technology among men than women.
The Ecole de technologie superieure hosts two new research chairs on artificial intelligence applied to health. The chairs aim to train qualified personnel who can work in a field combining AI and healthcare. Researchers plan to develop algorithms that improve real-time assessment of patient status and reduce ICU readmission rates.
A new AI tool developed by researchers at the University of Waterloo uses deep-learning technology to assess the severity of lung infections in COVID-19 patients. The tool shows promising results, aligning well with expert assessments and potentially improving clinical efficiency.
Researchers developed a brand reputation tracker that can monitor changes in brand reputation over time using artificial intelligence-based text analysis of social media posts. The tracker accurately reflected major brand events, such as changes in Facebook's reputation after the Cambridge Analytica scandal.
The Regenstrief Institute emphasizes the importance of algorithmic performance in healthcare, highlighting the need for systematic surveillance and vigilance to address inherent biases. Studies have shown that debiasing methods can help address disparities represented in data used to develop AI approaches.
Politecnico di Milano researchers used neural networks to predict the acoustic behavior of violin plates based on geometric parameters. The results showed an accuracy close to 98%, enabling luthiers to design and build violins with optimal sound quality, exploring new designs and materials.
The study used a slap on the hand as a test subject to examine reflexes and their coordination. The researchers found that humans anticipate pain when reacting to potential harm, which could be applied to robot development for improved safety. Robots can learn from human reflex systems to develop intelligent protective mechanisms.
Researchers at DESY have achieved two critical milestones in developing innovative plasma accelerators. By combining nitrogen and artificial intelligence, they significantly reduced the energy distribution of accelerated electron bunches, a crucial property for various applications. The team also successfully used AI to optimize the ac...
A UTA civil engineering professor is leading a $2.8 million project to analyze the condition and remaining service life of over 3,500 lane miles through TxDOT. The team will use AI, finite element modeling, and advanced spectroscopy tools to predict pavement lifespan.
A team of researchers at TUM developed a new early warning system for self-driving cars using artificial intelligence to learn from thousands of real traffic situations. The system can predict potentially critical situations with over 85% accuracy, up to seven seconds in advance.