Articles tagged with Artificial Intelligence
Geoffroy Hautier, a materials scientist at Rice University, has been elected a fellow of the American Physical Society for his groundbreaking research in high-throughput computational materials design and discovery. His work bridges quantum mechanics, computation, and artificial intelligence to accelerate the discovery of new materials...
Research highlights AI scams targeting Latino population with deepfake, voice-cloning and AI voice bots. Technical writing courses can help increase AI literacy and detect deception.
Researchers tested an AI-supported diagnostic method at rural hospitals in Kenya and Tanzania, analyzing cervical cell samples and human papilloma virus (HPV) samples using digital tools. The study found that the AI method worked well technically but faced challenges with inconsistent images and follow-up care.
Researchers from Shanghai Jiao Tong University and Hong Kong universities develop a comprehensive review on advanced AI chip design, focusing on energy efficiency, processing speed, and hardware scalability. The work provides a strategic roadmap for the development of high-performance AI chips through interdisciplinary collaboration.
Researchers at Texas A&M University have developed a new framework to protect industrial processing facilities from cyber threats. The framework identifies vulnerabilities, detects abnormal activity in real-time, and provides safeguards and mitigation strategies to maintain safe operations.
Plant functional diversity varies greatly depending on seasonal cycles and wet-dry periods, according to a new study that analyzed 4,000 satellite images. The researchers used AI algorithms to derive plant traits from the images and calculated quantitative measures of functional diversity.
A council of five AI models trained to deliberate together achieved higher accuracy on medical licensing exams than any single chatbot alone. This collaborative approach showed promise for improving the reliability and trustworthiness of AI tools in healthcare.
A new approach called Streamlined Life Cycle Assessment (SLCA) uses AI, 3D modeling, and secondary databases to assess a product's environmental footprint. SLCA cuts the time required for assessments from months to just one week, while maintaining accuracy.
Researchers developed an AI-based generative approach to discovering technology opportunities from patent maps using machine learning. The system translates patent vacancies into human-readable text, enabling the identification of untapped technologies and facilitating innovation forecasting.
Researchers at the University of Tokyo developed an AI-based framework, scHDeepInsight, to rapidly and consistently identify immune cells from gene data. The system uses hierarchical learning and image-based representation to distinguish broad and fine subtypes with improved accuracy and consistency.
Researchers at Harvard Medical School developed Dr. CaBot, an AI system that can generate a differential diagnosis and explain its nuanced reasoning like an expert diagnostician. The system reached a comparable final diagnosis to a human expert in a published case presentation, demonstrating its potential for medical educators and phys...
Researchers developed DeMemSeg, an AI-driven pipeline that accurately segments overlapping membrane structures with accuracy comparable to expert manual analysis. The approach enables large-scale, objective, and quantitative analysis of morphological data, providing a foundational technology for advancing disease mechanisms.
A new study uses general-purpose AI to classify real cosmic events and explain its reasoning without complex training. The model achieved approximately 93% accuracy and provided plain-English explanations for every classification.
The Indo-Swiss Workshop on 'Research Integrity in the Age of AI' brought together policymakers, scientists, and publishers to explore responsible AI use. Frontiers shared its pioneering approach to detecting research fraud using human-in-the-loop AI systems.
Researchers at NC State University identified a hardware vulnerability that allows attackers to compromise AI privacy by exploiting ML accelerator behavior. The GATEBLEED vulnerability exploits power gating in AI accelerators, creating an observable timing channel for attackers.
Researchers have developed an AI model that creates a detailed map of the mouse brain featuring 1,300 regions/subregions. The CellTransformer model uses spatial transcriptomics data to identify previously uncharted subregions of the brain, opening new avenues for neuroscience exploration.
Researchers use AI, omics, and systems biology to design targeted drugs for cardiovascular disease pathways. The tools could transform heart drug development and save lives, but global health policy leadership is urgently needed.
Scientists at MIT developed a method to predict how plasma in a tokamak will behave during rampdown, achieving high accuracy with limited data. This new model could significantly improve the safety and reliability of future fusion power plants.
Researchers at MIT have developed a 3D-printable aluminum alloy that is five times stronger than traditionally manufactured versions. This breakthrough could lead to lighter and more efficient aircraft parts, such as fan blades in jet engines, reducing energy consumption and costs.
The research team's Cord-Approx strategy coordinates drivers to assign different street parking spots using statistical predictions and an optimal matching algorithm. This approach significantly reduces parking search time, with drivers finding a spot in 6.7 minutes on average.
Paul Boutros, a pioneer in using AI and machine learning to analyze cancer data, is appointed as the new director of the National Cancer Institute-designated cancer center at Sanford Burnham Prebys. The cancer center will leverage computational tools to personalize therapies for cancer patients.
Researchers at Virginia Tech have developed an AI-powered system to detect flaws in wire-arc additive manufacturing, a faster approach to producing complex components. The technology enables real-time defect detection and correction, reducing waste and improving quality.
Researchers are developing sophisticated formulas to enable AI to interpret massive biological datasets and uncover disease insights. Dr. Xinlei Wang's team is creating AI models that can analyze complex biomedical data using a Bayesian framework, producing clear and interpretable results.
Researchers at the University of Sydney have developed end-to-end encryption for git services, protecting sensitive code from cybersecurity threats. The encryption aligns seamlessly with existing platforms like Github and Bitbucket, reducing computational resources needed while encrypting only edits.
A team of researchers from Worcester Polytechnic Institute has developed a new approach to producing hydrogen using plasma technology and metal alloys. The method reduces energy consumption and carbon emissions compared to traditional methods, making it more environmentally friendly and potentially affordable.
An AI-driven irrigation management system developed by Texas A&M University students uses soil sensors, crop data, and weather forecasts to optimize watering. The system conserves water, reduces costs, and increases crop yields, addressing global issues of water scarcity and inequity.
Researchers have discovered a new antibiotic targeting IBD, with AI predicting its mechanism of action. The AI model successfully identified the drug's target protein complex, reducing the development time by over two years and costs to $60,000.
A study by the American College of Surgeons found that AI enhanced evacuation efficiency, optimized routes, and prioritized patients by injury severity. AI also accelerated drug delivery, identified new treatments for injuries, and supported artificial limb selection.
A study by Osaka Metropolitan University found that pairs outperformed individuals in a robotic arm-transporting task when roles naturally emerged. Role specialization was key to superior performance, rather than paired interaction. The research has implications for human-robot collaboration and rehabilitation settings.
Researchers designed and lab-validated synthetic proteins using generative AI tools, outperforming natural proteins in editing the human genome. The study's findings have significant implications for improving gene editing tools and developing new therapies for cancer and rare diseases.
Mayo Clinic's new program enables biopharma companies to accelerate clinical development by providing access to de-identified data, advanced AI tools, and a global distribution network. This collaboration streamlines access to Mayo Clinic's world-class research expertise, allowing companies to move efficiently from discovery to delivery.
A new study from Hanbat National University demonstrates how quantum reinforcement learning can optimize residential heating, ventilation, and air conditioning systems for improved energy efficiency and indoor air quality. The technology reduces power consumption by up to 63% and decreases electricity costs by up to 64%.
The study found that AI scribes significantly reduced burnout, cognitive task load, and time spent documenting, allowing more time for meaningful work and professional well-being. The findings suggest that AI can help alleviate administrative burdens and improve patient access to care.
Researchers argue that AI can strengthen pandemic preparedness by detecting emerging diseases earlier. By combining data from humans, animals, and the environment, AI can reveal patterns and provide insights into potential pathogens.
A recent study reveals that large language models have been used in nearly a quarter of corporate press releases in 2024. The researchers found an increasing trend in the use of AI-assisted writing across various sectors, with significant growth in UN and US press releases.
A new analysis found that virtual reality effectively reduced anxiety during coronary angiography and had more stable vital signs than standard care. VR was superior to standard care in reducing anxiety and associated with significantly lower changes in heart rate and blood pressure.
Researchers at Tohoku University utilized AI to develop strategies for water treatment and air pollution control. The study highlights innovative approaches using machine learning in material screening and global distribution simulation of pollutants.
Large language models like ChatGPT are more persuasive than humans, especially when convincing people to adopt veganism or attend graduate school. The AI's ability to provide concrete logistical support and use authority-boosting vocabulary contributes to its persuasiveness.
Researchers from Florida Atlantic University's Charles E. Schmidt College of Medicine conducted a scoping review on AI-driven systems designed to deliver motivational interviewing. The study found that most used AI tools were chatbots, with varying levels of fidelity to core principles like empathy and autonomy.
A new 'future-guided' AI method developed at the University of California, Santa Cruz, has shown significant improvements in predicting seizures using brain wave data. The technique operates with two deep learning models working together, improving predictions further into the future by transferring knowledge.
Despite no decrease in usage, Wikipedia faces challenges from AI data scrapers and Large Language Models. The platform is struggling to allocate resources due to the influx of AI training data, threatening its current structure.
A new AI system called Diag2Diag analyzes sensor data to provide synthetic information for failing or degraded sensors in fusion systems, enhancing robustness and reducing complexity. This technology has the potential to make fusion energy more economical and reliable, enabling 24/7 operation without interruption.
Researchers at Champalimaud Centre for the Unknown used machine learning techniques to show that mice's facial movements reflect their hidden thoughts. This discovery could offer unprecedented insight into brain function and potential new research tools.
Researchers created a high-resolution 3D liquefaction hazard map using machine learning and geotechnical data. The model accurately predicted soil properties and liquefaction risk, identifying high-risk areas in reclaimed coastal zones and river floodplains with unprecedented clarity and precision.
A groundbreaking study enrolls 465 AYA cancer patients to test if chatbot technology and digital education tools increase uptake of genetic counseling and improve patient outcomes. The trial aims to address longstanding gaps in genetic services for AYAs aged 18-39, who often receive care with limited access to genetic specialists.
A new study published in AIAS found that warm red lighting can significantly reduce motion sickness in passengers during nighttime journeys. The research team conducted nighttime road tests and combined subjective ratings with multimodal physiological signals to assess symptoms.
An AI model successfully automates lymph node segmentation and extranodal extension classification from pretreatment CT scans in HPV-associated oropharyngeal carcinoma. Predicted extranodal extension is independently associated with worse oncologic outcomes, highlighting the potential for improved treatment planning.
Research presented at the European Emergency Medicine Congress finds that doctors and nurses are more accurate than AI in triaging patients in emergency departments. While AI showed some promise in flagging critical cases, its overall accuracy was lower than clinicians' across most metrics.
The startup has assessed over 3,400 miles of Indiana roads using advanced computer vision algorithms to quickly and objectively assess pavement conditions. This platform provides actionable insights without requiring in-house data analysis expertise or costly hardware.
A new AI tool called Waldo can scan social media data to discover personal reports of harmful side effects of popular health products. The tool achieved an accuracy of 99.7% in detecting adverse events, outperforming general-purpose chatbots.
Liberate AI project develops an AI model capable of predicting long-term outcomes and potential complications in ischemic stroke patients. The model will be trained using Swarm Learning technology, aiming for explainability and transparency, while striking a balance between these features and accuracy.
Researchers at The University of Osaka developed a reinforcement learning framework to enable spoken dialogue systems to acquire new vocabulary efficiently while minimizing user interruption. This approach improves word segmentation performance while reducing the number of questions asked.
A Harvard Medical School-led research team developed an AI tool called PICTURE that can reliably tell apart glioblastoma and primary central nervous system lymphoma during surgery. The tool distinguishes between the two cancers with near-perfect accuracy, reducing errors in diagnosis and guiding critical treatment decisions.
A new study aims to develop more fair and transparent AI interview systems using psychological measurement principles. Researchers will examine bias at three levels: predictors, outcomes, and perceptions of job seekers.
A recent study found that social benefit recipients have significant reservations about AI-supported decisions, rejecting them more frequently than non-recipients. The study also revealed that non-recipients systematically overestimate the willingness of affected individuals to trust AI.
Researchers at Institute of Science Tokyo developed a new framework for generative diffusion models by reinterpreting Schrödinger bridge models as variational autoencoders. This approach reduces computational costs and prevents overfitting, enabling more efficient generative AI models with broad applicability.
A National Science Foundation grant will support older adults in developing digital technology skills and embracing AI, with a focus on intergenerational storytelling. The project aims to strengthen AI literacy, social connectedness, and resilience among older adults, while cultivating responsible AI awareness in youth.
The new method eliminates the need for extensive AI training or optimization, making video layer editing faster, cheaper, and more accessible. OmnimatteZero preserves complex elements like fur, hair, foliage, shadows, reflections, smoke, or rippling water without current methods' limitations.
A new study found that AI tool accurately captures details in just three minutes from a body scan, highlighting the potential of using AI to repurpose data from routine scans. Visceral adipose tissue volume and fat deposits in muscle are strongly associated with diabetes and cardiovascular disease risk.
Researchers developed AI-powered BlinkWise glasses that track blinking patterns to assess fatigue, mental workload, and eye-related health issues. The device uses radio signals to detect minute eyelid movements with unprecedented detail, preserving privacy and using minimal power.