Articles tagged with Artificial Intelligence
A €10M Horizon Europe grant will support the development of a clinical decision support tool using artificial intelligence to select the best treatment for each individual patient with high blood pressure. The project aims to improve patient care and reduce avoidable consequences such as heart attacks, strokes, and kidney disease.
Researchers have developed a computer-assisted method to automate the assessment of speech severity in ataxia patients, achieving an 80% hit rate. The new methodology leverages artificial intelligence and could simplify procedures for determining ataxia severity, facilitating research and clinical practice.
A study at ECCMID shows AI software can detect TB from chest X-rays with sensitivity and specificity comparable to that of trained radiologists. The technology has the potential to improve diagnosis in low-resource settings where radiologists are scarce.
A new machine learning framework called MILI enables accurate multi-person 3D pose and shape representation from low-resolution images. The approach tackles occlusion issues in multi-person scenes with an occlusion-aware mask prediction network.
Researchers developed an AI algorithm that allows electronic devices to express uncertainty when faced with unexpected data, improving cough detection technology. The new approach enables more precise detection with fewer sound samples per second, reducing computing power and addressing privacy concerns.
Researchers developed a nano-excitonic transistor that controls excitons to process massive amounts of data at the speed of light with minimal heat energy loss. This technology has potential applications in optical computing and realizing an era of data explosion driven by AI.
A new AI stop smoking app, Quit Sense, detected triggers and provided support to help smokers manage urges to smoke in specific locations. The study found that four times more people who used the app quit smoking six months later compared to those only offered online NHS support.
A WVU research team has created an OPTIMAL model to help students overcome fears of learning code and enhance critical thinking skills when using ChatGPT, a popular AI chatbot. The model facilitates chatbot-aided scientific data analysis and aims to improve coding skills and prompting abilities.
A team of scientists at Max Planck Institute for the Science of Light developed a method to quickly and accurately diagnose cancer using artificial intelligence and real-time deformability cytometry. The method reduces analysis time from hours to under 30 minutes, enabling faster decision-making during surgery.
Newcastle University researchers have developed environmentally-friendly photovoltaic cells that harness ambient light to power IoT devices. The cells achieve an unprecedented power conversion efficiency of 38% and are non-toxic, setting a new standard for sustainable energy sources.
The new AI system, AI-Descartes, combines theory and data to discover scientific equations, reproducing key parts of Langmuir's Nobel Prize-winning work. It also rediscovered Kepler's third law of planetary motion and approximated Einstein's relativistic time-dilation law.
Prasanna Balaprakash has been named director of ORNL's Artificial Intelligence Initiative, focusing on developing foundational, scalable, and applied technologies. The initiative aims to advance breakthroughs in materials science, biology, health science, and nuclear engineering using AI and high-performance computing.
A team of scientists created a new, fast, and precise method for analyzing cells in tissue samples from cancer patients without the need for a trained pathologist. The method uses artificial intelligence to evaluate data produced by a technique called real-time deformability cytometry.
A study published in Scientific Reports found that ChatGPT's statements can significantly influence users' moral judgements. Participants were presented with moral dilemmas and asked whether the statement they read influenced their answers.
Researchers analyzed 1.5 million patients with 53 million electronic notes to identify 9,477 distinct phenotypes and demonstrated a high degree of agreement with expert judgment in various clinical fields.
Researchers at Carnegie Mellon University developed Pix2pix3d, a machine learning tool that generates realistic 3D representations of 2D sketches. The tool allows users to create customized 3D models for various applications, including video games and consumer products.
A new study published in Nature finds that artificial intelligence (AI) surpasses human sonographers in accurately assessing cardiac function from echocardiogram studies. The research, conducted at the Smidt Heart Institute, demonstrates AI's potential to improve the quality and effectiveness of heart evaluations.
A new AI-powered worklist reprioritization tool has been shown to significantly reduce both report turnaround time and wait time for pulmonary embolus-positive CT pulmonary angiography examinations. The study found a reduction of 47.6 minutes in report turnaround time and 21.4 minutes in wait time, with no significant difference in rea...
A study by Cornell University researchers found that using AI in conversations improves communication efficiency and positive emotional language, but participants perceive their partner as less cooperative when suspected of using AI-suggested responses.
Researchers developed AI predicting heatwaves using 'deep learning' and statistical models, providing a probabilistic approach up to a month before arrival. The technology is trained on 8,000 years of weather data and combines with rare event simulation algorithms for improved forecasts
In a new study, NC State University researchers had high school students develop their own machine-learning AI models to analyze data. The project aimed to prepare students for the future workforce and help them understand the potential and challenges of AI. Students created text classification models using StoryQ technology, which all...
A recent Baycrest study found that older adults are less able to distinguish between computer-generated and human speech compared to younger counterparts. This diminished ability could be related to older adults' reduced capacity to recognize emotions in speech, highlighting the need for AI-related training programs.
The University of Huddersfield has launched a smart rolling stock maintenance research facility to investigate cutting-edge technologies for improving the efficiency and reliability of train maintenance. The facility aims to reduce costs, increase reliability, and make rail travel more affordable.
A study on robot deception found that participants were overly trusting of AI and required explicit admission of lying in apologies to repair trust. Apologies that did not admit to deception were more effective at repairing trust, suggesting a need for designers to understand the ramifications of their design choices.
A new study by Cedars-Sinai investigators found that ChatGPT can provide easy-to-understand information about basic knowledge, lifestyle, and treatments for cirrhosis and liver cancer. The AI system has the potential to play a role in clinical practice and empower patients with knowledge about their disease.
A new AI tool, CLEAN, can predict enzyme functions based on amino acid sequences, outperforming leading state-of-the-art tools in accuracy and reliability. The tool was developed using contrastive learning and verified experimentally with both computational and in vitro experiments.
MIT researchers discovered unconventional activation functions that enable optimal neural network performance, leading to better classification on various datasets. The findings suggest that selecting the correct activation function can significantly improve data accuracy in machine learning applications.
Researchers at NIST have developed a new method of digitally simulating hurricanes using AI techniques, accurately representing the trajectory and wind speeds of real storms. The simulations can help develop improved guidelines for building design in hurricane-prone regions.
Researchers at USC have developed a new type of chip with the best memory of any chip thus far for edge AI. The chip uses metal oxide memristors to store information in a compact and stable way, eliminating the von Neumann bottleneck in current computing systems.
A recent study from Brigham Young University proves that artificial intelligence can respond to complex survey questions just like a real human. The researchers found high correspondence between how AI and humans voted in 2012, 2016, and 2020 U.S. presidential elections.
Researchers from the Smidt Heart Institute found that individuals with spherical hearts are 31% more likely to develop atrial fibrillation and 24% more likely to develop cardiomyopathy. The study identified four genes associated with cardiomyopathy and a greater risk of developing atrial fibrillation.
A University of Central Florida professor led a study identifying six challenges humans must overcome to ensure reliable, safe, trustworthy, and compatible AI. The challenges include responsible design, privacy protection, and respectful interaction with human cognitive capacities.
Assistant Professor Reza Ahmadzadeh at UMass Lowell has been awarded a $500,000 NSF CAREER grant to develop new algorithms for robots to learn complex tasks. The project aims to improve robot performance in everyday tasks, enabling them to assist older adults with daily chores and automate difficult duties in the workplace.
A new article in The Journal of Nuclear Medicine explores the potential for using ChatGPT, an artificial intelligence chatbot, in nuclear medicine and molecular imaging. The authors discuss the strengths and weaknesses of current AI bots and highlight the benefits of collaborating with AI allies to cope with increasing workloads.
Researchers have developed a multidisciplinary approach using a new microscope, artificial intelligence algorithm, and voltage indicators to better measure brain activity. The technique enables the imaging of up to 100 neurons at a time, far surpassing previous limits.
The TANGO project seeks to establish a symbiotic relationship between humans and machines, enabling effective and innovative AI systems that expand human reasoning and decision-making capabilities. Real-world use cases will be evaluated to assess the framework's potential impact on individuals and society.
Researchers developed an AI-based diagnostic screening system called DeepGlioma to analyze tumor specimens and detect genetic mutations rapidly. The system identified molecular subgroups with high accuracy and has the potential to improve access and speed of diagnosis for patients with deadly brain tumors.
Astrophysicists used AI to improve mass estimates of galaxy clusters by adding a simple term to an existing equation. The new equation downplays the importance of complex cores in calculations, providing more reliable mass inferences.
An international team used AI to analyze old star chemical abundances and found indications that the first stars formed in groups. The study suggests that first-generation stars must have been clustered together rather than isolated, offering a new constraint on the multiplicity of the first stars.
Scholars developed an AI program using symbolic regression to improve mass inferences of galaxy clusters. The new equations extract jelly at the center and concentrate on doughy outskirts for reliable mass inferences.
A new study using ChatGPT highlights the challenges of AI in academia, including concerns over academic dishonesty. However, researchers believe that AI can also be leveraged to improve education by automating administrative tasks and adapting assessments.
Researchers developed a computer model based on human brain mechanisms to improve speech comprehension. The model extracts multilevel information from ongoing speech and uses non-linguistic knowledge for disambiguating word meanings. This approach is more human-like than existing language models like ChatGPT.
Researchers developed a new method to collect data on animal behaviour and environment using drones and computer vision. The method allows for the extraction of information on spatial distribution, movement, and behaviour, providing rich insights into the social and environmental context of group-living animals.
Researchers developed a novel design for the chip using a crossbar layout, outperforming state-of-the-art photonic counterparts in terms of scalability and technical versatility. The synergy of powerful photonics with the novel crossbar architecture enables next generation neuromorphic computing engines.
A recent NC State University study examines the relationship between artificial intelligence (AI) and law enforcement. The study reveals that law enforcement agencies must be involved in developing public policies regarding AI technologies, such as autonomous vehicles. Key findings also suggest that many officers lack understanding of ...
Researchers developed an AI tool called SILIC to identify 169 species, including 137 birds, from bird sounds in Yushan National Park. The dataset provides detailed acoustic activity patterns of wildlife across short and long temporal scales.
An international team developed a novel method for evaluating AI interpretability methods to decipher the basis of AI reasoning and possible biases. The approach helps users understand what influences AI results and whether they can be trusted, especially in medical applications where AI-powered decisions can impact health and lives.
Researchers develop unsupervised machine learning algorithm to classify osteosarcoma at diagnosis based on gene expression modules. This approach enables personalized treatment strategies for osteosarcoma patients.
A University of Illinois project uses AI-powered object recognition to quantify kernel damage in wheat, enabling faster disease analysis and improved resistance. The technology has shown promising results, with potential for an online portal to automate scoring and support breeders in their efforts to eliminate fusarium head blight.
Researchers developed a self-driven lab, AlphaFlow, that uses AI to optimize complex chemical reactions and discover new materials. The system significantly reduces the time needed to develop new chemistries from months to hours.
A team of dermatologists developed an AI model to detect complications from bacterial or viral infections in atopic dermatitis patients. The model distinguishes between eczema and skin lesions caused by blood cancer, improving patient management and health outcomes.
A team of researchers, led by UMass Lowell's Neil Shortland, is developing AI systems to help doctors triage patients in emergency situations. The project aims to identify the best human attributes that AI can mirror when making difficult decisions.
Researchers argue that Artificial Social Intelligence (ASI) is the next big frontier for AI. ASI requires social perception, Theory of Mind and social interaction to understand others' mental states and cooperate in shared tasks. The field needs a holistic approach mimicking human interaction.
The Meta-Semi algorithm achieves competitive performance on challenging semi-supervised learning tasks, such as CIFAR-100 and STL-10, with only one additional hyper-parameter to tune. This approach naturally yields a meta-learning formulation where the correctly pseudo-labeled data has a similar distribution to labeled data.
A study published in Radiology found that an AI tool can accurately identify normal and abnormal chest X-rays with a high degree of sensitivity. The tool identified abnormal chest X-rays with a 99.1% sensitivity rate, outperforming clinical board-certified radiologists.
The CONFIDENTIAL6G project aims to enhance the security and reliability of 6G networks, enabling their use in emerging AI tools and IoT devices. IMDEA Software Institute will contribute privacy-preserving computation technologies such as secure multi-party computation and homomorphic encryption.
Researchers explore how AI language models like ChatGPT understand and respond to user input, mirroring their users' intelligence. The Reverse Turing Test reveals that chatbots reflect the intelligence level of their interviewers, incorporating their biases into responses.
A novel AI architecture, relational reasoning network, accurately identifies anatomical landmarks in CT scans for orthodontic treatments. The model learns spatial relationships between landmarks without explicit image segmentation, achieving accuracy comparable to conventional methods.
The use of AI is improving diagnostic accuracy for digestive cancers, but challenges in data sharing and standardization hinder its widespread application. Researchers surveyed recent applications of AI to these deadly cancers, finding that AI can automate complex processes and detect patterns not visible to humans.
A new AI model developed at the University of British Columbia accurately predicts cancer patient survival using natural language processing to analyze oncologist notes. The model shows over 80% accuracy in predicting six-month, 36-month and 60-month survival rates.