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UrduThis week, Facebook announced it was relying on artificial intelligence to help evaluate whether certain posts violated its policies and should be labeled or removed. According to a new survey overseen by the University of Delaware, the public should be…
Tag: Artificial Intelligence
“Multitasking” AI Tool Extracts Cancer Data in Record Time
Digital cancer registries collect, manage, and store data on cancer patients to help identify trends in diagnoses and treatment. However, cancer pathology reports are complex. To better leverage data, scientists developed an artificial intelligence-based natural language processing tool to help extract information from textual pathology reports.
How Cedars-Sinai Predicts Number of COVID-19 Patients
When the novel coronavirus started spreading across the U.S., hospital leaders were faced with a unique challenge: How could they accurately forecast the number of patients who would need hospitalization when no one knew what to expect from this new disease? To answer this and other questions, the data science team at Cedars-Sinai developed a machine learning platform to predict staffing needs. The team adjusted the platform’s algorithms to forecast data points related to the novel coronavirus. Now the platform tracks local hospitalization volumes and the rate of confirmed COVID-19 cases, running multiple forecasting models to help anticipate and prepare for increasing COVID-19 patient volumes with an 85%-95% degree of accuracy.
Artificial intelligence could improve accuracy, efficiency of CT screening for COVID-19 diagnosis
Researchers at the University of Notre Dame are developing a new technique using artificial intelligence (AI) that would improve CT screening to more quickly identify patients with the coronavirus.
How Technological, Socioeconomic and Geopolitical Forces are Altering Everything We Know about Marketing
A new study examines technological, socioeconomic and geopolitical forces altering the marketing industry — including deepening consumer relationships — and the implications for marketing managers, educators and researchers.
NIH harnesses AI for COVID-19 diagnosis, treatment, and monitoring
NIH has launched an ambitious effort to use artificial intelligence, computation, and medical imaging to enable early disease detection, inform successful treatment strategies, and predict individual disease outcomes of COVID-19.
The University of Chicago is awarded a major federal contract to host a new COVID-19 medical imaging resource center
A new center hosted at the University of Chicago — co-led by the largest medical imaging professional organizations in the country — will help tackle the ongoing COVID-19 pandemic by curating a massive database of medical images to help better understand and treat the disease. The work is supported by a $20 million, two-year federal contract that could be renewable to $50 million over five years.
Virtual lecture series finale connects interns to ongoing COVID-19 research
Students attending the last 2020 Office of Science Summer Internship Virtual Lecture Series seminar learned about how national laboratories are coming together to fight COVID-19.
New machine learning method allows hospitals to share patient data — privately
Penn Medicine researchers have shown that federated learning is successful specifically in the context of brain imaging, by being able to analyze magnetic resonance imaging (MRI) scans of brain tumor patients and distinguish healthy brain tissue from cancerous regions.
Visual analytics tool plucks elusive patterns from elaborate datasets
An ORNL team developed CrossVis, an open-source, customizable visual analytics system that analyzes numerical, categorical and image-based data while providing multiple dynamic, coordinated views of these and other data types.
Artificial Intelligence Identifies Prostate Cancer with Near-Perfect Accuracy
Study reports 98% sensitivity and 97% specificity in recognizing and characterizing prostate cancer using an artificial intelligence (AI) program.
Deep learning algorithm identifies tumor subtypes based on routine histological images
Researchers at the University of Chicago Medicine Comprehensive Cancer Center, working with colleagues in Europe, created a deep learning algorithm that can infer molecular alterations directly from routine histology images across multiple common tumor types. The findings were published July 27 in Nature Cancer.
Doctors urge hospitals to become ‘artificial intelligence ready’
Disorganized efforts to implement artificial intelligence in hospitals could undermine the technology’s vast potential to benefit patients, the group warns.
Photon-Based Processing Units Enable More Complex Machine Learning
Machine learning performed by neural networks is a popular approach to developing artificial intelligence, as researchers aim to replicate brain functionalities for a variety of applications. A paper in the journal Applied Physics Reviews proposes a new approach to perform computations required by a neural network, using light instead of electricity. In this approach, a photonic tensor core performs multiplications of matrices in parallel, improving speed and efficiency of current deep learning paradigms.
Children with type 1 diabetes may have a less desirable gut bacteria composition
Children with type 1 diabetes have a less desirable gut microbiome composition which may play a role in the development of the disease, according to new research published in the Endocrine Society’s Journal of Clinical Endocrinology & Metabolism.
Predicting X-ray Absorption Spectra from Graphs
Scientists built a machine learning model that can rapidly predict how atoms absorb x-rays for materials science research.
New breakthrough by NUS researchers gives robots intelligent sensing abilities to carry out complex tasks
The novel system developed by National University of Singapore computer scientists and materials engineers combines an artificial brain system with human-like electronic skin, and vision sensors, to make robots smarter.
How a Minecraft Mod is Helping Build Smarter AI
Polycraft World, a modification of the video game Minecraft, was developed by University of Texas at Dallas researchers to teach chemistry and engineering. Now the game that allows players to build virtual worlds is serving as the foundation for federal research to develop smarter artificial intelligence (AI) technology.
UT Dallas researchers received a grant from the Defense Advanced Research Projects Agency (DARPA) to use Polycraft World to simulate dynamic and unexpected events that can be used to train AI systems — computer systems that emulate human cognition — to adapt to the unpredictable. The simulated scenarios could include changing weather or unfamiliar terrain. In response to the COVID-19 pandemic, researchers have added the threat of an infectious disease outbreak.
General Electric Healthcare Chooses UH to Clinically Evaluate First-of-its-kind Imaging System
University Hospitals Cleveland Medical Center physicians completed evaluation for the GE Healthcare Critical Care Suite, and the technology is now in daily clinical practice – flagging between seven to 15 collapsed lungs per day within the hospital. No one on the team could have predicted the onset of the COVID-19 pandemic, but this technology and future research with GEHC may enhance the capability to improve care for COVID-19 patients in the ICU. Critical Care Suite is now assisting in COVID and non-COVID patient care as the AMX 240 travels to intensive care units within the hospital.
Argonne to explore how digital twins may transform nuclear energy with $8 million from ARPA-E’s GEMINA program
ARPA-E’s GEMINA funding will allow Argonne’s nuclear scientists to partner with industry and develop tools for the advanced reactors of tomorrow.
The Eye, The Brain & The Auto: Call for Research Abstracts from Healthcare and Automotive Experts
The Detroit Institute of Ophthalmology, the research arm of the Henry Ford Health System Department of Ophthalmology, is accepting abstracts for The Eye, The Brain & The Auto 9th World Research Congress on Health and Modern Mobility: Autonomous Vehicles, Driver’s Fitness to Function, and Naturalistic Driving Methods to be held Dec. 7-8, 2020. This will be a virtual event.
What If People Use Autonomous Vehicles To Do Bad Things?
There’s a fairly large flaw in the way that programmers are currently addressing ethical concerns related to artificial intelligence and autonomous vehicles (AVs). Namely, existing approaches don’t account for the fact that people might try to use the AVs to do something bad.
Research reflects how AI sees through the looking glass
Intrigued by how reflection changes images in subtle and not-so-subtle ways, a team of Cornell University researchers used artificial intelligence to investigate what sets originals apart from their reflections. Their algorithms learned to pick up on unexpected clues such as hair parts, gaze direction and, surprisingly, beards – findings with implications for training machine learning models and detecting faked images.
Department of Energy awards $3.15 million to Argonne to support collaborations with industry
The U.S. Department of Energy (DOE) announced more than $33 million in funding for 82 projects aimed at advancing commercialization of promising energy technologies and strengthening partnerships between DOE’s National Laboratories and private-sector companies.
National Science Foundation Awards $5 Million to Develop Innovative AI Resource
The NSF has awarded the San Diego Supercomputer Center (SDSC) at UC San Diego a $5 million grant to develop a high-performance resource for conducting artificial intelligence (AI) research across a wide swath of science and engineering domains.
An ethical eye on AI – new mathematical idea reins in AI bias towards making unethical and costly commercial choices
Researchers from the University of Warwick, Imperial College London, EPFL (Lausanne) and Sciteb Ltd have found a mathematical means of helping regulators and business manage and police Artificial Intelligence systems’ biases towards making unethical, and potentially very costly and damaging commercial choices – an ethical eye on AI.
Researchers use machine learning to build COVID-19 predictions
Researchers at Binghamton University, State University of New York are using machine learning to track the coronavirus and predict where it might surge next.
X-ray vision and eavesdropping ensure quality
With an X-ray experiment at the European Synchrotron ESRF in Grenoble (France), Empa researchers were able to demonstrate how well their real-time acoustic monitoring of laser weld seams works. With almost 90 percent reliability, they detected the formation of unwanted pores that impair the quality of weld seams. Thanks to a special evaluation method based on artificial intelligence (AI), the detection process is completed in just 70 milliseconds.
Researchers Design COVID-19 Knowledge Base and Risk Assessment Tool Powered by Artificial Intelligence
Researchers are creating a knowledge base that includes information for modeling outbreak and mutation of COVID-19, which will serve as a benchmark for better understanding the spread of the virus. They also are developing a multi-source deep neural network-based predictive tool to combine demographics, policies, regional infections, and individual information for risk evaluation using graph/network to represent entities and their relationships. The entities are fully compatible to the Unified Medical Language System standard for convenient knowledge sharing.
Six Argonne researchers receive DOE Early Career Research Program awards
Argonne scientists Michael Bishof, Maria Chan, Marco Govini, Alessandro Lovato, Bogdan Nicolae and Stefan Wild have received funding for their research as part of DOE’s Early Career Research Program.
CIO Amber Boehnlein Takes Computing up a Notch
Computer scientists, software developers and system administrators are coming together under one roof in the newly established Computational Sciences and Technology Division at the Department of Energy’s Thomas Jefferson National Accelerator Facility. Amber Boehnlein, Jefferson Lab’s chief information officer, has been promoted to associate director for computational sciences and technology, heading up the new division.
Predicting Side Effects
At a glance:
• Scientists develop AI-based tool to predict adverse drug events
• Such events are responsible for some 2 million U.S. hospitalizations per year
• The free, open-source system could enable safer drug design, optimize drug safety
Cornell research powers Facebook’s new AI shopping tool
A new artificial intelligence system allowing shoppers on Facebook to identify characteristics of items in uploaded photographs is based on Cornell University computer vision research into fine-grained visual recognition.
NUS engineers quintuple the efficiency of moving data bits in silicon chips for artificial intelligence applications
New innovative circuit technique can transfer digital bits at five times lower power consumption than existing chips, prolonging battery life in AI-enabled systems
New imaging method tracks brain’s elusive networks
Understanding the source and network of signals as the brain functions is a central goal of brain research. Now, Carnegie Mellon engineers have created a system for high-density EEG imaging of the origin and path of normal and abnormal brain signals.
Mount Sinai Receives Microsoft AI for Health Grant to Support Center Dedicated to Data Science Discovery for COVID-19
Grant Will Enable Development of AI Tools to Enhance Care and Evidence-based Medicine for Treating COVID-19 Patients
‘Artificial Chemist’ Combines AI, Robotics to Conduct Autonomous R&D
Researchers have developed a technology called “Artificial Chemist,” which incorporates artificial intelligence and an automated system for performing chemical reactions to accelerate R&D and manufacturing of commercially desirable materials.
Deep learning system will monitor birds at solar facilities
The U.S. Department of Energy’s (DOE) Argonne National Laboratory has been awarded $1.3 million from DOE’s Solar Energy Technologies Office to develop technology that can cost-effectively monitor avian interactions with solar energy infrastructure.
Rutgers Expert Can Discuss Artificial Intelligence and Art
New Brunswick, N.J. (June 1, 2020) – Rutgers University–New Brunswick Professor Ahmed Elgammal is available for interviews on the future of art and creativity in the age of artificial intelligence (A.I.). “As artificial intelligence becomes an increasing part of our…
Calibrated approach to AI and deep learning models could more reliably diagnose and treat disease
In a recent preprint (available through Cornell University’s open access website arXiv), a team led by a Lawrence Livermore National Laboratory computer scientist proposes a novel deep learning approach aimed at improving the reliability of classifier models designed for predicting disease types from diagnostic images, with an additional goal of enabling interpretability by a medical expert without sacrificing accuracy. The approach uses a concept called confidence calibration, which systematically adjusts the model’s predictions to match the human expert’s expectations in the real world.
Tech Contest Seeks to Bolster Energy-Efficient, Language-Based AI Applications
A technology consortium has launched an industry-wide competition to jump-start the development of more energy-efficient, language-based AI applications.
Argonne offers mentorship and resources to students in Department of Energy-sponsored graduate student research
As part of the Department of Energy’s Office of Science Graduate Student Research (SCGSR) Program, 62 graduate students were chosen to conduct thesis research across the national laboratory complex, including 12 students at Argonne.
Augmented reality helps teens tackle anxiety, head on
World first research that will test the ability of augmented reality to improve the delivery of cognitive behavioural therapy (CBT) as a treatment for symptoms of childhood anxiety among kids with asthma.
ISPOR Holds Its First Completely Virtual Conference
ISPOR concluded its Virtual ISPOR 2020 conference yesterday—its first completely virtual conference. The conference was redesigned as an online event when the COVID-19 pandemic required a necessary cancellation of the in-person conference.
S&T researcher examines if AI have a mind of their own
A Missouri University of Science and Technology researcher is examining what is considered evidence of artificial intelligence having a “mind,” which will show when a person perceives AI actions as morally wrong.
How Big Data and Artificial Intelligence Can Help Improve Healthcare Decision Making
ISPOR held its second Virtual ISPOR 2020 plenary session this afternoon, “Health Economics and Outcomes Research and Clinical Decision Making—Advancing Meaningful Progress.”
Johns Hopkins Researchers to Use Machine Learning to Predict Heart Damage in COVID-19 Victims
Johns Hopkins researchers recently received a $195,000 Rapid Response Research grant from the National Science Foundation to, using machine learning, identify which COVID-19 patients are at risk of adverse cardiac events such as heart failure, sustained abnormal heartbeats, heart attacks, cardiogenic shock and death.
‘Like looking for a needle in a haystack’: the global hunt to find key molecule to block COVID-19
A molecular biologist from the University of South Australia is working with a world leader in artificial intelligence-based drug discovery to help find a molecule that could prevent the SARS-CoV-2 coronavirus strain causing COVID-19 from infecting human cells.
Artificial Intelligence Algorithm Can Rapidly Detect Severity of Common Blinding Eye Disease
A new artificial intelligence (AI) algorithm developed by researchers at New York Eye and Ear Infirmary of Mount Sinai (NYEE) can rapidly and accurately detect age-related macular degeneration (AMD), a leading cause of vision loss in the United States.
Physicists Go Out on a Limb to Advance AI Computing
Research findings published in Nature Communications outline how a national team of researchers supported by the DOE’s Office of Science opens up a new dimension of safe hardware for AI and neuromorphic computing.