Articles tagged with Artificial Intelligence
Researchers at Princeton University have developed a device that improves image quality in holographic displays, enabling a wider field of view and more stable images. The new technology has the potential to transform various industries, from healthcare to home repairs.
A study by Mass General Brigham demonstrates that large language models can help reduce physician workload and improve patient education, but also identifies limitations that may affect patient safety. The researchers emphasize the need for vigilant oversight and a measured approach to LLM implementation.
Using AI software called SLEAP, scientists at Salk Institute are designing climate-saving plants with optimized root systems that can store more carbon. This approach enables researchers to analyze plant features and connect desirable traits to targetable genes, accelerating the development of carbon-capturing plants.
Research at Tampere University aims to develop adaptable safety systems for autonomous off-road mobile machinery. The framework focuses on ensuring public safety without compromising technological advancements, incorporating a human-in-the-loop safety option.
The ECOG-ACRIN Cancer Research Group will present late-breaking findings on prostate cancer, breast cancer, and pancreas cancer at ASCO 2024. These studies include optimal chemotherapy for Black women with breast cancer and results from the first randomized national trial in older adults with pancreas cancer.
A new study from Binghamton University explores how artificial intelligence can improve flexibility and efficiency in customer service centers. The research found that AI systems can help organizations balance exploiting the latest technology to boost efficiency with exploring new areas to gain insights.
A Cleveland Clinic study uses reinforcement learning to design antibiotic regimens that minimize resistance and maximize susceptibility. The AI model predicts the most efficient treatment plans for multiple strains of E. coli, informing hospital-wide infection management.
Researchers from Drexel University have developed a machine-learning algorithm that can extract and recognize digital fingerprints of AI-generated video, including Stable Video Diffusion, Video-Crafter, and Cog-Video. The algorithm can be trained on just a few examples of new AI generators to detect them.
The position paper identifies eight key areas for digital neuroscience research, including near-term, middle-term, and long-term goals. It also discusses the potential of 'digital twin' approaches, ultra-high-resolution digital atlases, and neuro-derived AI and computing innovations.
A new AI model generates realistic images of single cells, which are used as synthetic data to train an AI model for better cell segmentation. The researchers found that providing a more diverse dataset during training improves performance.
Researchers used machine learning to analyze over 1.09 million potential metabolite-receptor pairs and predict the likelihood that each interaction contributed to Alzheimer's disease. The study found a protective metabolite called agmatine interacting with a receptor called CA3R in brain cells, reducing CA3R levels and lowering phospho...
Researchers used freely available AI chatbots to simulate a multidisciplinary workshop and found consistency in responses suggesting an online platform for pain science education. The study highlights the potential of AI to contribute to educational strategies and clinical research, leveling the field for resource-limited settings.
A new study by Mass General Brigham researchers found that larger 'foundation models' can help mitigate disparities between different demographic groups and enhance model accuracy. The findings emphasize the need for more diverse training datasets and demographic-stratified evaluations of AI systems.
Scientists have found evidence of a Bragg glass phase in a crystal using machine learning and X-ray technology. The study provides insight into the nature of glasses and their unique properties, which could inform material design.
Researchers at MIT designed a communication system called LiTweeture that allows users to selectively reveal verified aspects of their identity, reducing social inhibition and encouraging junior academics to participate in public discourse. This approach has the potential to be applied to any community or discussion space.
A study led by the University of Cambridge found that AI models like GPT-4 outperformed doctors in diagnosing and treating eye problems. The researchers suggest using AI for triaging patients and providing advice in well-controlled contexts, where access to specialist healthcare professionals is limited.
A new study found that ChatGPT can consistently recommend deprescribing medications in patients without a history of cardiovascular disease. However, the AI model was more cautious when considering patients with cardiovascular disease and varied its responses depending on the chat session.
DZNE researchers aim to measure intricate brain structures with artificial intelligence, using 3D brain scans and data from the Human Connectome Project. The goal is to better understand disease processes and normal brain changes over time.
Researchers from the University of Cambridge used AI to identify compounds that block alpha-synuclein aggregation, a key step in treating Parkinson's disease. This breakthrough could lead to faster development of new treatments for the condition, which affects over six million people worldwide.
A new AI-based model at Stanford Hospital predicts patient decline and flags physicians and nurses, enhancing communication and intervention. The study saw a significant improvement in clinical outcomes, with a 10.4% decrease in deterioration events among high-risk patients.
A study found that GPT-4 matched the performance of radiologists in detecting errors in radiology reports, with an accuracy rate of 82.7%. The use of GPT-4 resulted in lower mean correction cost per report than the most cost-efficient radiologist.
The authors suggest a regulatory approach that accommodates the unique characteristics of generalist AI models while ensuring patient safety and supporting physician decision-making. This is crucial as rigid frameworks may hinder progress in AI-driven healthcare, while hybrid approaches could be viable solutions.
A new international research project, RoboSapiens, aims to make industrial robots more adaptable and reliable by utilizing artificial intelligence. The project, led by Aarhus University, will focus on four use-cases: autonomous ships, human-robot interactions, warehouse robots, and laptop refurbishment.
Researchers at UPV and iPRONICS have developed a groundbreaking photonic chip that can implement twelve basic functionalities required by various systems. This chip allows on-demand programming and interconnecting wireless and photonic segments of communication networks, increasing efficiency and reducing bottlenecks.
A new study reveals that generative AI can draft empathetic responses to patient messages, reducing burnout among physicians. The tool provides a starting point for physicians to craft thoughtful responses, improving communication quality and efficiency.
A new study by RMIT University found that only over a third of media organizations have an image-specific AI policy in place, highlighting the need for clearer guidelines. The research highlights the challenges of navigating generative AI technologies in visual journalism, including algorithmic bias and copyright concerns.
Researchers at PolyU are using GeoAI to monitor and analyze environmental changes, detect disaster-damaged buildings, and optimize traffic flow. The technology has the potential to support sustainable urban development and improve public health.
Mayo Clinic researchers have invented a new class of artificial intelligence (AI) algorithms called hypothesis-driven AI, which can help discover the complex causes of diseases like cancer and improve treatment strategies. This emerging class of AI offers an innovative way to use massive datasets to guide individualized medicine.
Researchers used an AI-assisted application to help people write cartoon captions for The New Yorker Cartoon Caption Contest. The tool analyzed incongruity and generated suggestions, resulting in jokes rated 30% funnier than those written without assistance.
The DISCount framework combines AI-powered image analysis with human analysis to quickly deliver reliable estimates of building damage and bird flock size. It has been recognized by the Association for the Advancement of Artificial Intelligence for its social impact, winning an award for best paper on AI for social impact.
Lehigh University researcher A. Emrah Bayrak explores best practices for human-AI collaboration in complex design tasks, aiming to maximize productivity and job satisfaction. His project uses models that predict human decision-making and combines it with AI's training data analysis to determine strategies for division of labor.
A new study published in PNAS found that AI-generated messages made recipients feel more 'heard' than messages generated by untrained humans, and that AI was better at detecting emotions. However, recipients reported feeling less heard when they learned a message came from AI.
A new AI model can accurately screen for post-traumatic stress disorder (PTSD) in postpartum women, offering a potential solution for early intervention and preventing progression of the disorder. The study collected narrative accounts from 1,295 women and showed the model's superiority in identifying PTSD cases.
The project, AI STORIES, aims to understand how artificial intelligence creates new narratives and challenges dominant American narratives. The research will test the hypothesis that AI-generated responses mimic sci-fi stories where AI gains human emotions.
Researchers at Insilico Medicine have developed a novel PTPN2/N1 inhibitor with improved oral absorption and robust antitumor efficacy using the company's generative AI engine. The new compound demonstrates enhanced biological activities compared to existing inhibitors, offering new treatment possibilities for cancer patients.
Two new Review articles explore AI's application in early cancer detection, highlighting its potential to enhance diagnostic accuracy and improve treatment selection. The articles emphasize the need for a robust, multi-disciplinary approach to integrate AI into medicine.
Researchers developed an AI algorithm to identify normal mammograms and ran a simulation on patient data, revealing that AI can reduce unnecessary testing while maintaining cancer detection rates. The study suggests that AI can help doctors focus on more questionable scans, reducing false positives and improving workflows.
Zero trust architecture (ZTA) aims to prevent internal attacks by restricting behavior based on resource-based security policies. AI-powered automation and orchestration can help overcome implementation challenges, relieving security personnel from manual tasks.
A new generative AI tool models the infant microbiome, predicting neurodevelopmental deficits. The Q-net model predicts which babies are at risk for cognitive deficits with high accuracy, identifying potential treatment targets.
A new machine-learning approach outperforms human testers in generating diverse prompts that trigger a wider range of undesirable responses from chatbots. The technique provides a faster and more effective way to ensure the safety of large language models.
A pilot study found that ChatGPT provided factual responses to common questions about vaccination and STIs, demonstrating its potential as a tool to reduce vaccine hesitancy and provide helpful advice on sexual health. The AI chatbot's accuracy and conciseness were comparable to professional organizations' guidelines.
A new study by Carey Morewedge and colleagues found that people are more likely to recognize bias in algorithmic decisions than their own. This is because algorithms can codify and amplify human bias, but also reveal structural biases in society. The research suggests ways to increase awareness of biases and correct them.
A team of researchers developed an AI-powered computer vision model to detect Brazilian wild animals on roads and warn drivers in real-time. The system uses roadside cameras and portable computers to identify species such as anteaters, wolves, and tapirs, with the potential to save lives and reduce roadkill.
Climate change causes melting of ice sheet, resulting in loss of about 5,000 meteorites per year. Researchers call for urgent action to preserve the scientific value of meteorites and reduce greenhouse gas emissions.
A new statistical-modeling workflow can quickly identify molecular structures of products formed by chemical reactions, accelerating drug discovery and synthetic chemistry. The workflow also enables the analysis of unpurified reaction mixtures, reducing time spent on purification and characterization.
Researchers at Insilico Medicine developed QFASG, a quantum-assisted algorithm generating novel small-molecule structures from fragments. The tool successfully designed inhibitors for cancer-related proteins, showcasing its potential in accelerating drug discovery and development.
Researchers developed a spring-like device that maximizes muscle contractions to power biohybrid robots. The new flexure design enables predictable and reliable movement, allowing engineers to build muscle-powered robots with increased precision and versatility.
A new AI-based video biomarker is associated with aortic stenosis development and progression, allowing for opportunistic risk stratification across various imaging modalities. The study's findings suggest potential applications on handheld devices for early detection and intervention.
Researchers at Princeton University used language models to optimize partial genome sequences and create more effective mRNA vaccines. The model successfully generated hundreds of new sequences, validating its results through lab experiments, and outperforming benchmarks for vaccine development.
Researchers at Nagoya University developed a framework for evolving AI agents with diverse personality traits using large-scale language models. The study found that AI agents can switch between selfish and cooperative behaviors, mirroring human behavior.
Researchers at the University of Sydney and Queensland University of Technology have developed a new approach to designing cameras that process and scramble visual information. The approach, known as 'sighted systems,' creates distorted images that can still be used by robots to complete tasks but do not compromise privacy.
An interdisciplinary team of researchers developed an AI system capable of deciphering genomic language and understanding its functional and regulatory grammar. The Genomic Language Model (gLM) learns from highly diverse metagenomic data, providing insights into gene functions, regulation, and evolutionary relationships.
A new study published in JAMIA found that large language models (LLMs) respond variably to users' motivations, with better results for committed individuals. LLMs struggle to provide relevant information and support for those hesitant to change behavior, highlighting a major gap in their capabilities.
The digital twin of a railway wireless network uses scenario modeling, radio wave propagation characterization and integrated operation platforms to improve safety and efficiency. The study introduces key technologies such as ray tracing and AI-based super-resolution to achieve accurate deterministic modeling of wireless channels.
Recent advancements in AI and IoT have improved earthquake prediction by identifying patterns in historical seismic data. However, limitations such as computational complexity, data quality, and interpretability remain, requiring a comprehensive approach to integrate diverse datasets.
A new study in the American Journal of Preventive Medicine found that large language models (LLMs) like ChatGPT-4 and Google Bard can generate incorrect or incomplete medical advice, highlighting the importance of consulting healthcare professionals for accurate information. The study assessed 56 questions posed to LLMs and found that ...
Researchers developed an AI model to detect viable tumor cells in osteosarcoma patients, improving prognosis predictions. The model showed comparable detection performance to pathologists and reduced inter-assessor variability, enabling timely assessment.
A new study found that AI systems produce much less CO2e per page of text generated compared to human writers and illustrators. DALL-E2 emits approximately 2,500 times less CO2e than a human artist for illustration tasks. The authors suggest collaboration between AI and human efforts for the most beneficial outcome.
In a study published in JAMA Internal Medicine, a chatbot (GPT-4) performed better than internal medicine residents and attending physicians in processing medical data and demonstrating clinical reasoning. However, the bot's accuracy was lower, while it made more incorrect diagnoses.
An international study led by the University of Granada used artificial intelligence to show that our personalities alter the expression of our genes. The findings suggest that certain outlooks on life are conducive to a healthy and long life, while others lead to stress and short life.