Articles tagged with Artificial Intelligence
Khalessi will shape UC San Diego Health's innovation strategy and lead the integration of new technologies, including AI. He aims to accelerate innovations supporting clinicians, patient safety, and operational efficiency.
A recent study published in Nature Communications found that the human brain processes spoken language in a sequence mirroring advanced AI language models. The research suggests that artificial intelligence can offer insights into how the brain constructs meaning, challenging traditional rule-based theories.
A new model developed by Osaka Metropolitan University Assistant Professor Takuya Fujinaga enables robots to accurately pick tomatoes, with an 81% success rate. The system evaluates the ease of harvesting for each tomato, taking into account factors such as fruit clustering and stem geometry.
Researchers at Stanford University have successfully used machine-learning-based control to operate a robot on the International Space Station, allowing for faster and more efficient navigation while maintaining safety. The system, which includes a warm start feature, enables robots like Astrobee to move through complex environments wi...
A new machine learning model developed at the University of Michigan uses data from wearable sensors to predict how physical therapists would assess balance training performance. The model was trained with sensor data combined with analysis from physical therapists and predicted patients' balance ratings with nearly 90% accuracy.
A new AI-based method can differentiate between tumour progression and radiation necrosis with high accuracy, enabling more accurate identification and treatment of late-stage cancer patients. This discovery could lead to better treatments for brain metastasis patients treated with stereotactic radiosurgery.
A University of Warwick-led analysis of 4,820 student reports found that student writing has become more sophisticated, formal, and positive since the introduction of ChatGPT in 2022. However, grades have remained stable despite stylistic shifts, suggesting core academic skills remain essential.
A study finds that most people trust doctors more than AI for health diagnoses, but have a positive view of AI's potential in cancer diagnosis. The research used two nationally representative surveys to assess public attitudes toward AI in healthcare, including trust, understanding, and excitement.
A breakthrough AI system called OmniPredict can predict human pedestrian behaviors with unprecedented accuracy, revolutionizing self-driving cars and urban mobility. The model combines visual cues with contextual information to anticipate pedestrians' next moves, reducing the risk of accidents and improving traffic safety.
The University of Phoenix College of Doctoral Studies has released a new white paper exploring the leadership opportunities for AI to increase employee value. The authors suggest that leaders can redesign roles, address skills gaps, and unlock higher-value work with generative AI.
The Battery Large Model system revolutionizes battery design, manufacturing, operation, and recycling through AI-simulation synergy. It provides a novel technological path for the industry's intelligent upgrade, enabling autonomous design scheme generation, accurate performance prediction, and intelligent defect detection.
Researchers propose AI-based surrogate brain framework that integrates forward modeling, inverse problem solving, and evaluation to build next-generation data-driven models. The framework enables applications such as predicting future whole-brain activity, performing dynamical systems analysis, and guiding neurostimulation strategies.
A new study presented at the 2025 American Society of Hematology meeting revealed that subtle disruptions in genome architecture can predispose individuals to lymphoma. The research found that damaged 3D genome architecture can silence key tumor suppressor genes, creating fertile ground for malignancy.
The SECURED project aims to provide a secure environment for decentralized, cooperative processing of health data and anonymisation assessment. The consortium is developing AI models to diagnose and treat patients with blood malignancies in a secure way, ensuring patient data protection and compliance with European privacy regulations.
A new study analyzes 183 scientific publications to highlight gaps in AI research for STEM education. The analysis reveals a technocentric approach that neglects non-cognitive skills, ethical issues, and geographical diversity.
A new study from Michigan Medicine found that its data-driven command center increased hospital bed use efficiency by 63%, reducing emergency department boarding time by 33% and patient transfers by 13%. The initiative also streamlined discharge processes, resulting in a 12% drop in waiting times for patients ready to leave the hospital.
A new AI model can accurately identify brain abnormalities in MRI scans for various conditions, including stroke, multiple sclerosis, and brain tumors. The model can also triage scans, increase reporting speeds, and support clinical decision-making by suggesting findings to radiologists.
A new UNC-Chapel Hill study uses large language models to accelerate georeferencing in plant specimen collections, unlocking millions of records for global ecological research. The breakthrough technology improves upon traditional methods with near-human accuracy and efficiency.
IMDEA Networks has created a secure watermarking tool called FreqyWM, allowing institutions to tag their data with a unique signature and preventing leaks and unauthorized copies. The tool enables the exchange and reuse of information while complying with legal frameworks on security and privacy.
The symposium will feature experts sharing cutting-edge research and insights on AI in clinical settings, aiming to improve chronic health outcomes and expand access to mental healthcare globally. The event is a unique platform for networking and collaboration, highlighting innovative approaches that move the field forward.
New research from Cornell University finds that AI chatbots powered by large language models can effectively persuade voters in either direction, shifting opinions by significant margins. The models' persuasiveness comes from providing many factual claims supporting their arguments, but these claims are not necessarily accurate.
Researchers at MD Anderson have made significant discoveries in the treatment of rare bile duct cancers, with zanidatamab showing promising results. Additionally, a study identified RASH3D19 as a target to overcome treatment resistance in KRAS-mutant cancers.
A11yShape, an AI-assisted tool, enables visually impaired computer programmers to create, edit and verify complex 3D models without assistance. The tool uses GPT-4o to provide detailed descriptions of the model for blind and low-vision programmers.
Researchers developed instance-adaptive scaling framework that uses process reward model to estimate difficulty of question, enabling LLMs to spend more compute on promising solution paths. This approach achieves comparable accuracy with existing methods while reducing computational cost by up to one-half.
The MIT team developed a new AI-based controller that enables the robot to follow gymnastic flight paths, such as executing continuous body flips. The robot's speed and acceleration increased by 450% and 250%, respectively, compared to previous demonstrations, making it comparable to insects in terms of agility.
A survey of UK journalists found that most (56%) use AI weekly, while 27% use it daily. However, concerns remain, with 62% viewing AI as a threat to journalism. The study also revealed a gap between independent and large corporate media outlets in their adoption of AI.
The EBRAINS Summit 2025 will bring together experts to assess how neuroscience can drive medical progress, digital innovation, and responsible data use. Preliminary results from the EPINOV clinical trial, integrating virtual brain technology for epilepsy surgery planning, will be presented.
A researcher warns that AI can distort our perceptions of death and existence by blurring presence and absence. He suggests that embracing selfless selves, or interconnectedness, can help us accept impermanence and the inevitability of death.
The University of Leicester, in partnership with TWI Ltd, has secured £560k to develop a robot-mounted arc-welding system for in-space repair and manufacturing. The project aims to overcome the challenges of welding in space by developing a new, space-qualified robotic welding capability.
Researchers found that complexity can lead to bias in AI models, highlighting the need for better modeling of real-world complexities, input from diverse groups, and ground truths. By addressing these factors, developers can create more accurate and fair AI systems.
A new study by Cambridge University Press & Assessment and Microsoft Research found that traditional learning activities like making notes remain critical for students' reading comprehension and retention. Note-taking, either alone or combined with large language models (LLMs), was more effective in helping students understand and reme...
The article reviews how AI is addressing challenges in metasurface technology, from unit-cell optimization to system-level integration. AI-driven methods like graph neural networks and multi-task learning enhance stability and performance against manufacturing variations.
Researchers at Pusan National University have developed an AI-powered design methodology for gerotor pumps, achieving a 32.3% increase in average flow rate and reducing pressure fluctuation by 53.6%. This innovation has the potential to improve engine durability, lubrication, and cooling, leading to quieter operation and increased reli...
Large language models (LLMs) exhibit network formation behaviors similar to humans, including preferential attachment, triadic closure, and homophily. In real-world simulations, LLMs prioritize homophily most strongly, followed by triadic closure and preferential attachment.
Researchers at Tokyo University of Science propose approximate domain unlearning (ADU) algorithm, which differentiates between domains while preserving generalization capability. This approach enables flexible AI configuration suited to individual practical scenarios.
The conference will bring together thousands of experts to share research and attend sessions on the latest Computer, Big Data and Artificial Intelligence developments. Authors can submit full research papers and benefit from a registration fee waiver for selected outstanding papers.
University of Missouri researchers are combining in-home sensor technology with artificial intelligence to monitor daily changes in ALS patients' health. The system uses machine learning to estimate a patient's score on the ALS Functional Rating Scale Revised, predicting potential problems before they occur.
A monitoring system devised by the University of Córdoba uses AI algorithms to predict flowering stages with high precision. This allows beekeepers to optimize their harvesting times and reduce losses, as well as track health issues and other potential problems without visiting the apiary.
The team created a specialized two-dimensional thin film dielectric designed to replace traditional heat-generating components in integrated circuit chips. This breakthrough aims to reduce the significant energy cost and heat produced by high-performance computing necessary for AI.
A study compares five DNA foundation language models across 57 diverse datasets to identify their strengths and weaknesses in predicting gene expression, identifying genomic components, and detecting harmful mutations. The findings highlight the importance of selecting appropriate models based on specific genomic tasks.
Researchers introduce a new nanoscale optical device made of molybdenum diselenide that entangles the spin of photons and electrons, enabling quantum communication. The technology has the potential to create low-cost, low-energy quantum components for secure data transmission.
The ARU symposium delves into the effects of consuming mass-produced low-quality content, reshaping art, media, politics, and the internet. Dr Tina Kendall discusses the psychological and societal implications of AI-generated material, including its environmental costs.
GenAI tools risk eroding medical students' critical thinking skills while reinforcing data bias and inequity. Medical educators must adjust curricula to mitigate these risks, warns an editorial in BMJ Evidence Based Medicine.
A new tool trained on videos of expert surgeons offers students personalized advice as they practice suturing, showing significant improvement in skills. The AI model incorporates explainable AI to provide detailed feedback, enabling meaningful self-training and scaling up medical training.
A new AI system can accurately reconstruct hand muscle activity without sensors, enabling precise estimation of fine motor control. The technology has potential applications in sports science, rehabilitation, and human-machine interaction.
Researchers developed FocalCodec, an audio tokenization method that compresses speech efficiently, preserving its meaning and sound quality. The system was tested with positive results, showing nearly identical reconstructed speech to original recordings.
Insilico Medicine will demonstrate how generative AI is accelerating therapeutic discovery, improving drug efficacy, and advancing personalized medicine. The company's pharma superintelligence platform aims to tackle challenging problems in modern science and medicine.
Researchers from Johns Hopkins University found that selecting the right blueprint can accelerate learning in visual AI systems, rivalling conventional methods. By modifying convolutional neural networks, they generated brain-like activity patterns, suggesting that architectural design plays a crucial role in AI development.
A new study benchmarks six prompt styles across three leading LLMs to solve the challenge of balancing accuracy, speed, and cost in structured data workflows. The research reveals distinct strengths in each model, highlighting the need for tailored approaches for different data types.
A team of researchers has developed a detailed open map of emerging technologies, grouping 23,000 plus technologies into a multi-level map. The Cosmos 1.0 framework uses machine learning to analyze Wikipedia pages, books, and patents.
Researchers developed a reduced order model that accelerates calculations by identifying key features in flow data, enabling faster testing of geometry parameters for efficiency gains. The team plans to make their extensive database and model available online for other research groups.
A new tool reorders content to downrank posts containing antidemocratic attitudes and partisan animosity, reducing polarization. Users who had such content downranked showed more positive views of the opposing party, with a noticeable impact on their emotional responses.
A new AI image-only model has been shown to provide stronger and more precise risk stratification for five-year breast cancer prediction than traditional breast density assessment. The model was trained on 421,499 mammograms and showed a fourfold higher cancer incidence in high-risk women compared to those with average risk.
A randomized clinical trial conducted at UCLA Health found that AI scribe tools reduced physician documentation time by 9.5% and improved burnout scores. While the technology showed promise, it also generated clinically significant inaccuracies and required active physician oversight.
Researchers analyzed clips from Hollywood films to identify brain structures linking visual and tactile experiences. They discovered eight remarkably similar maps in the visual cortex, mirroring the body's organization in the somatosensory cortex.
Researchers at Institute of Science Tokyo developed a neural-network-based 3D imaging technique that can precisely measure moving objects. The new method reconstructs high-resolution 3D shapes using only three projection patterns, enabling dynamic 3D measurement across various applications.
The SUN-DT project aims to drive the digital transition of tower concentrated solar power (CSP) plants in Europe. By leveraging AI-based calibration, predictive maintenance, and real-time optimization, the initiative seeks to improve efficiency and reduce operational costs for these facilities.
Researchers propose six dimensions to evaluate AI reliability, including transparency, uncertainty quantification, and philosophical perspectives on trustworthiness. They emphasize the need for critical understanding of AI systems to ensure trustworthy decision-making.
Researchers developed a deep learning model to measure adrenal gland volume on existing CT scans, identifying the first imaging biomarker of chronic stress. The AI-derived biomarker correlates with validated stress questionnaires, cortisol levels, and future cardiovascular outcomes.
A recent study by Dr. Hyungrae Noh critiques traditional moral frameworks for ascribing responsibility to human stakeholders and AI systems, instead proposing a distributed model of responsibility where duties are shared among both. The study emphasizes the need for human stakeholders to prevent AI from causing harm through monitoring ...