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UrduBiological components are less reliable than electrical ones, and rather than instantaneously receive the incoming signals, the signals arrive with a variety of delays.
Tag: Machine Learning
New AI models of plasma heating lead to important corrections in computer code used for fusion research
New artificial intelligence models for plasma heating can do more than was previously thought possible, not only increasing the prediction speed 10 million times while preserving accuracy but also correctly predicting plasma heating in cases where the original numerical code failed.
Research to use machine learning to ’reverse-engineer’ new composite materials
Professors at Binghamton University, State University of New York have received NSF grant for deep-learning model that can customize microarchitecture based on specific needs
Bar-Ilan University researchers available for comment on Nobel Prize winning research in physics
The following experts in physics, brain science, computer science and additional fields can comment on the awarding of the Nobel Prize in Physics for 2024 to U.S. scientist John Hopfield and British-Canadian Geoffrey Hinton for their discoveries and inventions that laid the…
AIP Congratulates 2024 Nobel Prize Winners in Physics
The 2024 Nobel Prize in physics was awarded to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”
Implementing medical imaging AI: issues to consider
As AI is deployed in clinical centers across the U.S., one important consideration is to assure that models are fair and perform equally across patient groups and populations. To better understand the fairness of medical imaging AI, a team of researchers trained over 3,000 models spanning multiple model configurations, algorithms, and clinical tasks.
Inaugural summit to explore artificial intelligence
A new virtual conference will explore how artificial intelligence (AI) can help health care providers and scientists efficiently analyze vast amounts of data and make more informed decisions, the Endocrine Society announced today.
Feet First: AI Reveals How Infants Connect with Their World
Researchers explored how infants act purposefully by attaching a colorful mobile to their foot and tracking movements with a Vicon 3D motion capture system. The study tested AI’s ability to detect changes in infant movement patterns. Findings showed that AI techniques, especially the deep learning model 2D-CapsNet, effectively classified different stages of behavior. Notably, foot movements varied significantly. Looking at how AI classification accuracy changes for each baby gives researchers a new way to understand when and how they start to engage with the world.
New AI model efficiently reaches clinical-expert-level accuracy in complex medical scans
UCLA researchers have developed a deep-learning framework that teaches itself quickly to automatically analyze and diagnose MRIs and other 3D medical images – with accuracy matching that of medical specialists in a fraction of the time.
Replacing hype about artificial intelligence with accurate measurements of success
A new paper in Nature Machine Intelligence notes that journal articles reporting how well machine learning models solve certain kinds of equations are often overly optimistic. The researchers suggest two rules for reporting results and systemic changes to encourage clarity and accuracy in reporting.
Ceevra 3D Models Improve Outcomes for Patients Undergoing Prostate Cancer Surgery
In a multisite randomized controlled trial published in JAMA Network Open in September 2024, the use of Ceevra 3D models in robotic prostatectomy procedures were shown to reduce risk of cancer recurrence, improve functional outcomes, and improve rates of trifecta outcomes.
Postdoc Takes Multipronged Approach to Muon Detection
2024 JSA Postdoctoral Prize Winner Debaditya Biswas will combine different particle identification methods with machine learning to detect muons hidden in a sea of pions.
Department of Energy Announces $68 Million in Funding for Artificial Intelligence for Scientific Research
The use of Artificial Intelligence (AI) in scientific research is a top priority at the Department of Energy (DOE), which today announced $68 million in funding for 11 multi-institution projects, comprising 43 awards.
Using AI to prevent ruptured brain aneurysms
Bioengineering Ph.D. student Holly Berns won a grant from the Brain Aneurysm Foundation to study how AI and other new technologies can change how aneurysms are discovered and treated. Her project will use AI and machine learning to examine how arteries leading to the brain are tilted and whether that tilt contributes to the formation and rupture of brain aneurysms.
FAU Engineering Professor Achieves Milestone as Highly Cited Google Scholar
Dr. Khoshgoftaar’s scientific publications have garnered more than 63,500 citations during his distinguished career at FAU (1985 to present), yielding a Google Scholar h-index of 95.
Notre Dame researchers create new tool to analyze embodied carbon in more than 1 million buildings in Chicago
The impact of embodied carbon in the built environment has been difficult to assess, due to a lack of data. To address that knowledge gap, Ming Hu, the associate dean for research, scholarship and creative work in Notre Dame’s School of Architecture, and Siavash Ghorbany, a Notre Dame graduate student in civil and environmental engineering, have created a new tool to analyze the embodied carbon in more than 1 million buildings in Chicago. Their recently published research identifies 157 different architectural housing types in the city and provides the first ever visual analysis tool to evaluate embodied carbon at a granular level and to help inform policymakers seeking to strategically plan for urban carbon mitigation.
New tool detects fake, AI-produced scientific articles
A team including faculty at Binghamton University, State University of New York has created a machine-learning algorithm that can detect up to 94% of bogus academic papers — nearly twice as successfully as more common data-mining techniques.
$1.8M NIH Grant to FAU Engineering Fuels Quest to Decode Human Evolution
FAU has received a five-year NIH grant to further research on designing and applying statistical methods to identify regions of the genome affected by natural selection, which is an important evolutionary force that enables humans to adapt to new environments and fight disease-causing pathogens.
Machine learning predicts which patients will continue taking opioids after hand surgery
A machine learning algorithm performs well in predicting the risk of persistent opioid use after hand surgery, reports a study in the August issue of Plastic and Reconstructive Surgery®, the official medical journal of the American Society of Plastic Surgeons (ASPS). The journal is published in the Lippincott portfolio by Wolters Kluwer.
Swifter simulations for modern science. All of it
In a machine learning paper recently published in the journal npj Computational Materials, a team of researchers from Sandia National Laboratories and Brown University have introduced a universal way to accelerate virtually any kind of simulation.
Illinois researchers develop near-infrared spectroscopy models to analyze corn kernels, biomass
In the agricultural and food industry, determining the chemical composition of raw materials is important for production efficiency, application, and price. Traditional laboratory testing is time-consuming, complicated, and expensive. New research from the University of Illinois Urbana-Champaign demonstrates that near-infrared (NIR) spectroscopy and machine learning can provide quick, accurate, and cost-effective product analysis.
Using machine learning to speed up simulations of irregularly shaped particles
Researchers at the University of Illinois Urbana-Champaign have trained neural networks to predict interactions between irregularly shaped particles to accelerate molecular dynamics simulations.
Indagar en la mente de la inteligencia artificial para fabricar mejores antibióticos
La inteligencia artificial (IA) ha explotado en popularidad, pero al igual que un ser humano, es difícil leer la mente de la IA. La IA explicable (XAI), un subconjunto de la tecnología, podría ayudarnos a hacer justamente eso justificando las decisiones de un modelo.
Peering into the mind of artificial intelligence to make better antibiotics
Artificial intelligence (AI) has exploded in popularity, but it’s hard to know what’s going on inside. Explainable AI (XAI) gives justification for an AI model’s decisions, and now, researchers are using it to make better antibiotics. They will present their results at ACS Fall 2024.
President Joe Biden announces up to $23 million in funding for Tulane University to invent advanced cancer imaging system
President Joe Biden and First Lady Jill Biden will visit Tulane University to announce up to $23 million in funding to develop a cutting-edge cancer imaging system. This technology, led by Tulane researchers, aims to allow surgeons to detect and confirm the complete removal of tumors during surgery within minutes, reducing the need for repeated procedures.
Say ‘aah’ and get a diagnosis on the spot: is this the future of health?
A computer algorithm has achieved a 98% accuracy in predicting different diseases by analysing the colour of the human tongue.
Ships Now Spew Less Sulfur, but Warming Has Sped Up
New findings document fewer ship tracks, reduced cloud cover, and boosted warming after ship emissions regulations took effect in 2020.
Humans change their own behavior when training AI
Wash U researchers from multiple disciplines team up to study how human behavior changes when training AI
Engineers develop general, high-speed technology to model, understand catalytic reactions
A research team led by Iowa State’s Qi An has developed artificial intelligence technology that could find ways to improve researchers’ understanding of the chemical reactions involved in ammonia production and other complex chemical reactions.
Monitoring of nature reserves via social media and deep learning
Researchers from the National University of Singapore have created a deep learning method to analyse social media images taken within protected green spaces to gain insights on human activity distribution as a way to monitor the ecological impacts of these activities.
Will social media polls accurately predict the winner of the U.S. presidential election?
JungHwan Yang, a professor of communication at the University of Illinois Urbana-Champaign, is a co-principal investigator on a research project and a website — socialpolls.org — that examine the informal polls about the U.S. presidential election posted on the social media platform X, formerly…
Argonne’s AI Testbed gives researchers access to cutting-edge AI systems for science
The Argonne Leadership Computing Facility’s AI Testbed is a growing collection of some of the world’s most advanced AI accelerators available for open science.
New research shows how machine learning could revolutionize diagnosis and treatment of multiple myeloma and sepsis
Exciting research at the frontier of artificial intelligence and data science in laboratory medicine was presented today at ADLM 2024 (formerly the AACC Annual Scientific Meeting & Clinical Lab Expo).
Researchers develop state-of-the-art device to make artificial intelligence more energy efficient
Engineering researchers at the University of Minnesota Twin Cities have demonstrated a state-of-the-art hardware device that could reduce energy consumption for artificial intelligent (AI) computing applications by a factor of at least 1,000.
How Machine Learning Is Propelling Structural Biology
Cell biologist embraces new tools to study human development on the smallest scale
Advanced Deep Learning and UAV Imagery Boost Precision Agriculture for Future Food Security
A research team investigated the efficacy of AlexNet, an advanced Convolutional Neural Network (CNN) variant, for automatic crop classification using high-resolution aerial imagery from UAVs.
Scientists develop new artificial intelligence method to create material ‘fingerprints’
Researchers at the Advanced Photon Source and Center for Nanoscale Materials of the U.S. Department of Energy’s Argonne National Laboratory have developed a new technique that pairs artificial intelligence and X-ray science.
Predictive models for photosynthetic active radiation irradiance in temperate climates
Abstract This research evaluated 10 different empirical models designed for predicting Photosynthetically Active Radiation (PAR) at higher latitudes, addressing atmospheric conditions specific to these regions. The research introduces the Musleh-Rahman (MR) model, which substitutes Diffuse Horziontal Irradiance (DHI) with Clear…
Study: Algorithms Used by Universities to Predict Student Success May Be Racially Biased
Predictive algorithms commonly used by colleges and universities to determine whether students will be successful may be racially biased against Black and Hispanic students, according to new research published today in AERA Open, a peer-reviewed journal of the American Educational Research Association.
Researchers develop an AI model that predicts Continuous Renal Replacement Therapy survival
A UCLA-led team has developed a machine-learning model that can predict with a high degree of accuracy the short-term survival of dialysis patients on Continuous Renal Replacement Therapy (CRRT).
Machine learning could aid efforts to answer long-standing astrophysical questions
PPPL physicists have developed a computer program incorporating machine learning that could help identify blobs of plasma in outer space known as plasmoids. In a novel twist, the program has been trained using simulated data.
New Radiative Transfer Modeling Framework Enhances Deep Learning for Plant Phenotyping
A research team has developed a radiative transfer modeling framework using Helios 3D plant modeling software to simulate RGB, multi-/hyperspectral, thermal, and depth camera images with fully resolved reference labels.
American College of Radiology Launches First Medical Practice Artificial Intelligence Quality Assurance Program
The American College of Radiology® (ACR®) today launched the ACR Recognized Center for Healthcare-AI (ARCH-AI), the first national artificial intelligence quality assurance program for radiology facilities. The program outlines building blocks of infrastructure, processes and governance in AI implementation in real-world practice.
Balancing Act: Novel Wearable Sensors and AI Transform Balance Assessment
Traditional methods to assess balance often suffer from subjectivity, aren’t comprehensive enough and can’t be administered remotely. They also are expensive and require specialized equipment and clinical expertise.
Easter Island’s ‘population crash’ never occurred, new research reveals
A detailed new analysis of Easter Island’s rock gardens by a research team including faculty at Binghamton University, State University of New York shows that a hypothetical “population crash” never occurred on the island.
How can AI cope with changing categories?
Bar-Ilan University researchers have uncovered a new universal law detailing how artificial neural networks handle an increasing number of categories for identification. This law demonstrates how the identification error rate of such networks increases with the number of required recognizable objects.
The role of institutions in early-stage entrepreneurship: An explainable artificial intelligence approach
Abstract Although the importance of institutional conditions in fostering entrepreneurship is well established, less is known about the dominance of institutional dimensions, their predictive ability, and more complex non-linear relationships. To overcome the limitations of traditional regression approaches in addressing…
Researchers harness AI for autonomous discovery and optimization of materials
Today, researchers are developing ways to accelerate discovery by combining automated experiments, artificial intelligence and high-performance computing. A novel tool developed at Oak Ridge National Laboratory that leverages those technologies has demonstrated that AI can influence materials synthesis and conduct associated experiments without human supervision.
Groundbreaking LLNL and BridgeBio Oncology Therapeutics collaboration announces start of human trials for supercomputing-discovered cancer drug
In a substantial milestone for supercomputing-aided drug design, Lawrence Livermore National Laboratory (LLNL) and BridgeBio Oncology Therapeutics (BridgeBio) today announced clinical trials have begun for a first-in-class medication that targets specific genetic mutations implicated in many types of cancer.
Mount Sinai Health System named 2024 Hearst Health Prize winner
Hearst Health and the UCLA Center for SMART Health awarded the 2024 Hearst Health Prize to Mount Sinai Health System. Mount Sinai Health System was declared the winner for a machine learning application called NutriScan AI that facilitates faster identification and treatment of malnutrition in hospitalized patients.