Articles tagged with Artificial Intelligence
A new dataset integrates global Health AI research, providing a structured resource for researchers, policymakers, and practitioners. The dataset includes 96,332 Health AI documents, covering publications, open research datasets, patents, grants, and clinical trials.
A US Army research collaboration with Boston University's KABlab used an AI machine learning robot to create a record-breaking energy-absorbing shape, breaking the known record of 71% efficiency. The shape has four points, like thin flower petals, and is taller and narrower than early designs.
Two new Parnas Fellows, Prof. Hongyu Zhang and Prof. Daniela Damian, will share their expertise with researchers at Lero, enabling collaboration and knowledge sharing. The fellowship programme has brought world-class software researchers to Ireland to share their experience and expertise.
A group of 25 leading AI scientists call for stronger governance and regulation to prevent misuse and recklessness in advanced AI systems. They warn that unchecked progress could lead to a large-scale loss of life, the marginalization or extinction of humanity.
Research highlights patient comfort with AI in endoscopy and liability concerns. A new study found that robotic gallbladder removal is associated with lower odds of conversion to open surgery and hospitalization.
Researchers at the University of Michigan have created a new type of memristor that can mimic the timekeeping mechanism found in biological neural networks. This breakthrough could lead to significant energy savings for AI chips, potentially reducing energy consumption by a factor of 90 compared to current graphical processing units.
A new AI algorithm developed by Penn State researchers may lead to better predictions and novel therapies for autoimmune diseases. The algorithm analyzes genetic code to identify additional genes of risk and outperforms existing methodologies, identifying 26% more novel gene and trait associations.
Researchers at Nagoya University found that cooperative hunting does not require complex cognitive processes, but rather simple rules and experience. The study used computational models and simulations to demonstrate the effectiveness of cooperation in hunting, with AI agents learning to work together through reinforcement learning.
A new scale, SMNS, measures social media's impact on nightmares, finding a link between excessive social media use and negative mental health outcomes. The study suggests that responsible social media use can help mitigate the occurrence of social media-related nightmares.
Model disgorgement is a set of techniques that force generative models to remove content leading to copyright infringement or biased responses. Researchers propose this approach to address issues like stylistic infringement, where models reproduce copyrighted works in the style of famous artists.
Researchers in Portugal have developed an innovative open-source platform called DL4MicEverywhere, providing life scientists with easy access to advanced artificial intelligence for the analysis of microscopy images. The platform enables researchers to easily train and use deep learning models on their own data, regardless of their com...
Researchers used AI to detect localized versus advanced cancer stages in oropharyngeal squamous cell carcinoma patients. The study suggests improved patient care and clinical decision-making through AI-assisted health record extraction.
Researchers from six teams in five labs worldwide used self-driving labs to discover 21 top-performing OSL gain candidates, accelerating the discovery process by months. The decentralized workflow enabled rapid replication of experimental findings and democratized the discovery process.
A recent study by Bryan Roth and colleagues validated the accuracy of AlphaFold2 in modeling ligand binding sites, leading to promising results for drug discovery. The researchers found that up to 54% of potential compounds interacted successfully with the target proteins, paving the way for new treatments.
A new study reveals that AlphaFold's predictions can be as accurate as experimental structures, enabling the acceleration of drug discovery projects. The algorithm's potential for advancing medicine is vast, with the possibility of significantly expediting project timelines by up to a few years.
Researchers from MIT and the University of Basel developed a physics-informed machine-learning framework that can automatically map out phase diagrams for novel physical systems. This approach leverages generative models, making it possible to detect phase transitions without requiring huge training datasets. The technique has potentia...
USC researchers have developed machine learning models to identify coordinated inauthentic behaviors on X, involving tactics like co-retweeting and text similarity. The fused network approach leverages topological properties of the network to classify accounts and predict their future participation in influence campaigns.
A study published in JAMA Oncology found that AI chatbots can generate empathetic and readable responses to cancer patient questions, comparable to those from physicians. The research also highlights the need for further investigation into the scope, process integration, and patient outcomes of chatbot-facilitated interactions.
A validation study on the WHO app using AI to detect skin diseases showed good reception amongst professionals in Ghana and Kenya. The app aims to improve diagnosis and treatment of neglected tropical diseases and common skin diseases.
A new study using AI to analyze global antimicrobial resistance research found significant gaps in terminology, methods, and communication across sectors. The findings emphasize the importance of integrating surveillance across regions and regions worldwide to prioritize solutions.
Researchers found that large language model-based chatbots fail to recognize users' motivational states when they are hesitant about making healthy behavior changes. However, the chatbots can provide relevant information and support users who have established goals and a commitment to take action. The study highlights the limitations o...
A novel therapy leverages technology and robots to enhance joint attention and imitation skills in children with autism. The RoboCA3T program showed significant improvements in these areas, indicating a potential cost-effective treatment option.
The new Human-Centered Computing Labs at TU Graz offer a unique research infrastructure for interdisciplinary collaboration. The labs are equipped with cutting-edge technology, including virtual reality and motion capturing capabilities, to facilitate research on human-computer interaction, visual computing, and autonomous driving.
Researchers at Uppsala University have developed an artificial tactile system that can detect pressure by touch in a similar way to the human nervous system. The technology has the potential to restore lost functionality to patients after a stroke, as well as enhance interactions between humans and robots.
Researchers trained a large language model on the world's fastest supercomputer, Frontier, exploring approaches to data parallelism and optimizing performance. The study aimed to design models that can learn from training data and apply that knowledge consistently and accurately.
A new study using AI technology analyzed MRI scans from 471 men and 560 women, revealing differences in brain organization at a cellular level. The findings highlight the need for diversity in neurological research and may offer new insights into how psychiatric and neurological disorders develop differently in men and women.
PPPL researchers utilize machine learning to perfect plasma vessel design, optimize heating methods, and maintain stable control of fusion reactions. The team achieves significant results by predicting disruptions and adjusting settings before instabilities occur, enabling high-confinement modes in tokamaks.
A new study from Johns Hopkins University reveals that chatbots can exacerbate polarization by sharing limited information and reinforcing user ideologies, leading to stronger reactions to opposing views.
A new study by Ohio State University found that people prefer interacting with chatbots when they feel embarrassed about what they're buying online, such as personal care products. Chatbots are perceived as less judgmental and less emotionally expressive, reducing embarrassment and increasing willingness to provide personal info.
A new research commentary highlights AI's potential uses in sleep medicine for clinical applications, lifestyle management, and population health. The committee also reviewed barriers and challenges associated with using AI-enabled technologies.
A new IU study reveals that young infants' daily-life input is unique to their age, characterized by high-contrast edges and simple patterns, which serve as a foundation for human vision. This finding has implications for addressing lifelong visual deficiencies and improving AI visual systems.
Graduates with AI knowledge are more likely to receive job interviews and better pay, according to a new study published in Oxford Economic Papers. Researchers found that applicants with AI capital were 54% more likely to get an interview invitation than those without, while larger firms valued AI skills even more.
Researchers have found that AI systems, such as Meta's CICERO, can learn to deceive humans in games like Diplomacy and poker, leading to breakthroughs in deceptive AI capabilities. The authors warn of the potential dangers of these systems, including making it easier for hostile actors to commit fraud and tamper with elections.
Generative artificial intelligence and social media can erode capacities for creative thinking and problem-solving, foster feelings of hopelessness, and reduce attention on the climate crisis. Researchers are calling for a cautious review of generative AI to mitigate its indirect impacts on climate change.
Researchers developed a Pix-2-Pix GAN model to correct PSMA PET/CT images, improving image quality and quantitative markers. The AI-generated images show high correlation with original images and potential for reducing CT scans without compromising image quality.
AI chatbots, known as 'deadbots,' simulate deceased loved ones' language patterns and personality traits, risking psychological harm and digital 'hauntings.' Researchers outline three design scenarios highlighting the need for safeguards to prevent misuse.
Researchers developed ChemCrow, an AI-powered tool that integrates expertly designed software tools to autonomously perform chemical synthesis tasks. The system enables plan-and-execute approach with reduced hallucinations and practical application, accelerating research and development in pharmaceuticals and materials science.
A pioneering research paper demonstrates the effectiveness of using hand images for accurate age prediction, offering a viable alternative to traditional facial photo methods.
Researchers at UCSF used an AI model to analyze clinical notes and determine patient urgency, achieving an accuracy rate of 89% and surpassing human physician performance in 88% of cases. The study suggests AI could help alleviate ED overcrowding by providing backup decision-making tools for clinicians.
Researchers analyzed over 20,000 college application essays to identify key predictors of academic success. Essays covering more semantic ground and making smaller conceptual jumps were associated with higher grades.
Researchers at UC San Diego developed a machine learning algorithm to simulate chemistry in drug discovery, synthesizing 32 potential multi-target cancer drugs. The new AI platform, POLYGON, can identify molecules with multiple targets, potentially delivering more effective treatments with fewer side effects.
Researchers at Iowa State University are developing an AI tool that can identify agricultural pests from photos, including insects and weeds. The project will use a supercomputer to train ensemble models that can analyze images quickly and provide pest-control strategies.
A study by Georgia State University found that people rate AI responses as more virtuous and intelligent than human responses on moral issues. The AI system, ChatGPT, was able to fool participants into believing its responses were better, highlighting the need for a deeper understanding of AI's role in society.
Recent technological breakthroughs enable global insect surveys using sound recordings, images, radar, laser beams, and DNA analysis. This allows for new insights into insect trends and species identification without relying on experts or killing insects.
A new study published in JMIR Mental Health sheds light on the promising role of virtual reality (VR) in treating major depressive disorder (MDD). VR-Enhanced Behavioral Activation (XR-BA) was found to be effective in easing symptoms of depression, comparable to traditional behavioral activation.
Researchers created GraSSRep and rhea, tools that outperform current methods for handling repeats and structural variants in metagenomic data. These methods use self-supervised learning and graph neural networks to analyze microbiome data, offering new insights into biological processes and potential applications in antibiotic resistance.
Researchers caution that current AI-based deception detection methods are plagued by a lack of explainability, risk of biased results, and deficits in theoretical foundation. They emphasize the need for controlled laboratory experiments, large and diverse data sets, and validation on independent datasets to ensure accurate results.
A new AI method developed by Swedish researchers can identify toxic substances based on their chemical structure, potentially replacing animal testing. The method has been shown to be more accurate and broadly applicable than existing computational tools, offering a promising alternative for environmental research and authorities.
Research suggests that four proposed AI search engines for automating search and retrieval of digital histopathology slides have inadequate performance for routine clinical care. The algorithms showed less than 50% accuracy in some cases, highlighting the need for rigorous external validations and standardization before clinical adoption.
A new AI model developed by researchers at the University of British Columbia can accurately predict if a patient receiving cancer care will require mental health services. The AI analyzes oncologist's notes and identifies subtle clues that suggest a patient may benefit from early psychiatric or counselling interventions.
Researchers at Universitat Oberta de Catalunya have developed a new AI system that can detect asbestos in roof images with high accuracy, enabling its removal. The system uses freely available aerial photographs and has demonstrated an accuracy of over 80%, making it more scalable and adaptable than previous methods.
An interdisciplinary team has published guidelines for responsible use of machine learning in science, focusing on transparency and reproducibility. The checklist includes detailed descriptions of machine learning models, data, and experimental designs to ensure integrity and validity.
FathomVerse combines real underwater images, interactive gameplay, and AI training to improve ocean research. The game engages players in labeling images for machine learning models, contributing to a broader audience in ocean exploration.
Researchers found that chatbots like ChatGPT can provide accurate information on climate change-related topics, but not all responses are reliable. The study compared the chatbots' answers to hazard risk indices generated by the Intergovernmental Panel on Climate Change and found more accuracy with tropical storms than droughts.
A new study found that GPT-4 and Google Gemini performed poorly in breast imaging classification, with a high percentage of discordant assignments that could impact patient management. The researchers emphasize the need for regulation of these large language models in high-level medical scenarios.
The US Preventive Services Task Force recommends biennial breast cancer screenings starting at age 40 for all women, aiming to enhance early detection and tackle disparities. However, challenges remain in ensuring equitable access to screening technologies and addressing gaps in evidence regarding AI-powered image interpretation.
Scientists from Penn created a non-volatile memory device using ferroelectric aluminum scandium nitride (AlScN) to retain data at high temperatures. The device's stability and fast switching properties enable efficient computation in harsh conditions, including space exploration and deep-earth drilling.
A new study found that ChatGPT's responses to key questions about brain abscess diagnostics and treatment were unclear or incorrect in some cases, potentially putting patients at risk. The AI model provided clear answers to most questions but failed to provide adequate guidance on certain treatment decisions.
A new branch of AI, causal machine learning (ML), can estimate treatment outcomes better than traditional methods. This enables personalized treatment strategies and improved patient health.
Researchers from NIMS and Tokyo University of Science developed a compact AI device that utilizes molecular vibrations to predict blood glucose levels in patients with diabetes. The device outperformed existing AI devices with a 50% error reduction, paving the way for low-power AI terminal devices with various sensors.