Articles tagged with Artificial Intelligence
Artificial intelligence enhances pandemic preparedness with AI-driven models for outbreak forecasting and optimizing resource allocation. AI accelerates vaccine development by identifying candidates through molecular simulations and designing clinical trials.
A Northwestern Polytechnical University team evaluated the performance of Gemini and GPT-series models across various medical tasks, finding strengths in report generation and lesion detection. The study highlights the potential of multimodal LLMs in alleviating clinician burden and integrating AI into clinical practice.
A new study from Vanderbilt University Medical Center shows that a clinical alerts-driven AI system can effectively prompt doctors to screen patients for suicide risk during regular clinic visits. The study found that interruptive alerts were more effective than passive alerts, leading to a 42% increase in screenings.
A new study published in Nature Medicine shows that AI-based models can accurately identify ovarian cancer in ultrasound images, achieving an accuracy rate of 86.3%. The models also reduce the need for expert referrals and misdiagnosis rates by 63% and 18%, respectively.
Researchers from KIT developed AI algorithms that can detect tumors efficiently and precisely. The algorithms are based on deep learning methods and have been shown to excel in the autoPET competition. Further research is needed to improve the algorithms and make them more resistant to external influences.
A new study evaluates AI's performance in real-world medical conversations and finds significant drops in diagnostic accuracy. Researchers designed a more realistic test called CRAFT-MD to assess the fitness of large-language models for use in clinics.
Researchers warn that AI assistants will combine intimate psychological and behavioral data with persuasive technologies to build trust and manipulate social behavior. The 'Intention Economy' could lead to a lucrative yet troubling marketplace where human intentions are commodified.
The Cambridge Handbook of the Law, Policy, and Regulation for Human-Robot Interaction addresses emerging issues in AI and robots, including privacy, safety, and regulation. The book offers valuable insights into ethical dilemmas and proposes solutions to balance enforceability and flexibility.
Researchers at Tokyo University of Agriculture and Technology developed an explainable AI model to classify videos of splashing and non-splashing drops. The model achieved a success rate of 92% for low-viscosity liquid and 100% for high-viscosity liquid, revealing key differences in droplet behavior during impact stages.
Researchers developed AI-driven therapeutic platform mimicking viral structures to deliver therapeutic genes to target cells. The innovative approach achieved precise symmetrical structures and effectively delivered payloads, paving the way for breakthroughs in gene therapies and next-generation vaccines.
A Stanford Medicine study found that AI can help researchers quickly evaluate large amounts of medical data, identifying trends and patterns. The tool was trained on notes from 1,201 children with ADHD, allowing researchers to pinpoint gaps in follow-up care and identify tactics to improve ADHD management.
Current energy-hungry transformer-based systems contrast with Turing's idea of machines that develop intelligence naturally, like human children. AI systems can now perform tasks exclusive to human intellect, such as generating coherent text and discussing abstract ideas, but with limitations on sustainability and societal impact
A new AI-driven approach identifies potentially harmful chemical substances in rivers by monitoring their effects on tiny water fleas, providing insights into complex mixtures and aquatic life. The study enables more comprehensive environmental monitoring and supports better-informed regulations for chemical discharge into waterways.
NCSA is leading the way in AI research support, partnering with the National Artificial Intelligence Research Resource Pilot and the NSF-Simons SkAI Institute. The organization is also working on healthcare projects like MarginDX, combining optical imaging technologies with AI screening tools to ensure accurate tumor removal during sur...
Researchers create SciAgents framework to autonomously generate and evaluate promising research hypotheses in biologically inspired materials. The framework uses graph reasoning methods to organize relationships between scientific concepts, mimicking biological systems.
Robert Johansson's Machine Psychology concept combines adaptive artificial intelligence with psychological learning principles to create a more intelligent AI system. The goal is to implement human-like intelligence in machines, enabling them to learn from experiences and apply knowledge across various situations.
A new AI system has been developed to detect compound-type dark jargons on social media, which are used by offenders to evade detection. The system achieves a 7% improvement in accuracy and identifies 93% of newly detected dark jargons as previously unknown, highlighting its potential to reveal emerging terms.
Researchers developed a laser-based artificial neuron that emulates biological graded neuron functions, achieving a signal processing speed of 10 GBaud. This enables fast AI decision-making in time-critical applications with high accuracy.
A new study by UCL researchers found that AI systems amplify human biases, leading to a snowball effect where small initial biases increase the risk of human error. The researchers demonstrated real-world consequences, including overestimating white men's likelihood of holding high-status jobs and underestimating women's performance.
A new study reveals that people tend to assign more blame to artificial intelligences perceived as having human-like minds. The researchers found that participants blamed the AI more than other parties involved in real-world moral transgressions, such as companies or governments.
A new set of internationally-agreed recommendations aims to reduce potential bias in medical AI technologies. The STANDING Together initiative recommends improving dataset diversity, inclusivity, and generalisability to ensure safe and effective use of AI for everyone. These guidelines are now available open access.
Researchers create multilayered chip design that doesn't require silicon wafer substrates, allowing for better communication and computation between layers. This breakthrough enables the construction of fast and powerful AI hardware comparable to supercomputers.
Researchers found that neural stem cells have a rejuvenating effect on nearby brain cells, while T cells promote stress and damage. The study opens new avenues for research into slowing or reversing brain aging.
Researchers at the University of Washington developed a new method called variational preference learning, which predicts users' preferences and tailors its outputs accordingly. This approach overcomes the limitations of traditional RLHF, which can lead to averaging user preferences and resulting in incorrect outputs for all users.
Researchers at MIT have developed Boltz-1, an open-source AI model that achieves state-of-the-art performance in predicting biomolecular structures. The model surpasses AlphaFold3, which is limited to academic research and commercial use, by incorporating new algorithms and improving prediction efficiency.
The AIRCARE Project will introduce AI-powered systems for real-time diagnosis and precision CO2 laser surgery, improving outcomes for UADT cancer patients. The project aims to reduce positive margins, enhance surgical precision and ease of use, transforming quality of life.
The Digital Health Institute aims to develop transformative solutions in digital health, including early detection, predictive analytics, and personalized medicine. The initiative will focus on research and development, as well as training the next generation of digital health leaders.
Combining AI and citizen science enhances SDG monitoring and achievement by addressing data gaps and biases. Successful applications have been demonstrated in addressing environmental indicators, good health, sustainable cities, life below water, and life on land. The integration of these approaches can create synergies to address sust...
Researchers from Florida Atlantic University developed an AI system that accurately detects and tracks American Sign Language alphabet gestures using computer vision. The model achieved a detection process with high accuracy, recognizing complex hand gestures with an F1 score of 99% and mAP of 98%.
Paulo Costa and Shou Matsumoto are developing an explainable artificial intelligence (AI) methodology to help decision-makers trust AI-generated strategies. The project aims to support hypothesis management and identify data requirements to address system complexity and opacity in complex environments.
A new screening method combining laser analysis with AI identifies patients with breast cancer in its earliest stage, stage 1a. This non-invasive technique reveals subtle changes in the bloodstream that occur during the initial phases of the disease, outperforming existing early detection strategies.
Northwestern University's expertise in AI and astrophysics enables the development of cutting-edge artificial intelligence tools for the Giant Magellan Telescope. The partnership will enhance the telescope's capabilities to search for Earth-like planets, investigate energetic explosions, and explore galaxy-black hole relationships.
A new AI image tool, INQUIRE, can aid in analyzing millions of wildlife images uploaded to the internet for insights into climate change impacts on species. Current AI algorithms can identify species but struggle with more complex questions.
A new AI tool called PlacentaVision can rapidly evaluate placentas at birth to detect abnormalities associated with infection and neonatal sepsis. This could lead to improved health outcomes for both mothers and babies, particularly in areas with limited medical resources.
A team of researchers has developed a novel technique to steal artificial intelligence (AI) models by monitoring electromagnetic signals. The method allows attackers to recreate the high-level features of an AI model with 99.91% accuracy, potentially undermining intellectual property rights and exposing sensitive data.
Researchers developed a new method, k* distribution method, to visualize and assess how well deep neural networks categorize related items together. The model reveals clustered, fractured or overlapping arrangements of data points, indicating accuracy and reliability issues.
The ChangeMaker K-12 program equips rising educators with skills to teach engineering and human-centered design to K-12 students. The program has already seen six cohorts of teacher candidates and over 200 students in grades 1-5 participate.
Researchers at George Mason University have received $1,049,998 in funding from the Patient-Centered Outcomes Research Institute (PCORI) to develop an AI system that helps patients find the right depression medications. The new study aims to address known challenges in AI and incorporate an empathetic tone.
Researchers developed a deep learning model that classifies pancreatic cancer into molecular subtypes using histopathology images, achieving high accuracy and rapid turnaround time. The AI tool has the potential to improve patient outcomes by enabling timely and tailored treatment strategies.
LangBiTe detects biases in AI responses, allowing users to define their own ethical concerns and adapt the evaluation of bias. The tool includes libraries with over 300 prompts focusing on specific ethical issues, such as ageism, LGBTIQA+phobia, and sexism.
A comprehensive benchmark evaluates statistical and engineering approaches to federated learning for healthcare applications. Statistical FL methods excel in non-predictive tasks, while engineering-based FL algorithms demonstrate superior predictive performance.
A pioneering study using AI interviewing platform has shed light on young Singaporeans' hopes, fears, and unique perspectives on family planning decisions. Key findings indicate that financial concerns are the top barrier to having children, with work-life balance and mental readiness also being significant concerns.
A new technique identifies and removes specific points in a training dataset that contribute most to a model's failures on minority subgroups. This approach maintains the overall accuracy of the model while improving its performance regarding underrepresented groups.
Researchers at Drexel University developed an AI tool using large language models to identify and suggest alternative words that stigmatize people with substance use disorder. This framework aims to educate users and preserve supportive spaces in online forums.
The study found that integrating AI into sales teams requires sales managers to combine traditional interpersonal communication competence with new AI-related skills. Effective communication involves motivation, knowledge, empathy, and adaptability, as well as crafting effective prompts to AI and maintaining a polite tone.
A groundbreaking AI model called NitroFusion creates images in seconds using modest hardware, eliminating the need for large computing resources. The open-source technology enables creative professionals and individuals to produce high-quality images affordably.
Researchers have developed an AI framework called XLuminA that autonomously discovers new experimental designs in microscopy. The framework performs optimizations 10,000 times faster than well-established methods, opening the path for exploring completely new territories in microscopy.
A new system, EXPLINGO, enables AI models to generate readable narratives explaining their predictions, helping users make better decisions. The system, developed by MIT researchers, uses large language models to transform complex explanations into plain language and automatically evaluate their quality.
Researchers trained an AI system to predict future warming based on climate model simulations and historical temperature data. The study suggests that even in the best-case scenario, global warming will likely exceed 2 degrees Celsius, with severe impacts expected in regions such as South Asia and Central Europe.
Researchers from Bar-Ilan University discover that classifying objects together through Multi-Label Classification can yield better results than detecting individual objects. This new method allows networks to learn correlations between object combinations, making them more recognizable in real-life applications such as autonomous vehi...
A study of 9,000 US-based participants reveals that they prioritize efficiency over fairness when choosing between human and algorithmic decision-makers. Notably, Republicans prefer humans more than Democrats, yet most claim fairness is a top priority.
A new shape-changing device called Shape has been developed to help people with visual impairment perform a location task as effectively as sighted people. The study found that participants with visual impairment located targets significantly faster using Shape than with vibration technology, and preferred it over current methods.
A recent study by ESMT Berlin scholars presents a comprehensive framework detailing the impact of AI on open innovation. The framework highlights three key ways in which AI is transforming open innovation practices: enhancing existing methods through efficiency and scalability, enabling new forms of collaboration and business models, a...
Cell culture medium optimization is crucial for effective growth of cells, as the medium determines the culture results. Researchers developed a machine learning model that optimizes the composition of the medium based on training data, achieving higher cell concentrations than commercially available media.
Scripps Research scientists created an AI model called MovieNet that processes videos by mirroring brain processes, recognizing visual scenes and distinguishing subtle changes. This breakthrough has the potential to transform fields like medical diagnostics, autonomous driving and more.
The new AI framework, DIMON, solves ubiquitous math problems known as partial differential equations in nearly all scientific and engineering research. It enables faster prediction of solutions for complex engineering designs, such as crash testing, orthopedics research, and bridge stress resistance.
Two studies found that readers perceive a lower level of credibility in news produced with AI assistance, regardless of whether they understand the extent of AI's involvement. Readers attribute human contributions more value than AI-driven content.
Researchers at Tokyo University of Science have developed a new method called black-box forgetting, which enables selective removal of unnecessary information from large pre-trained AI models. This approach enhances model efficiency and improves privacy by reducing computational resources and information leakage.
Professor Gerhard Neumann at KIT has received a EUR 2.4 million ERC Consolidator Grant to improve robots' ability to perform complex tasks in real environments. His SMARTI³ project aims to develop intuitive interfaces and scalable capabilities for complex manipulation tasks.
A recent study by the Society for Risk Analysis found that employees who visit adult or gambling sites are more likely to encounter seven types of malware, including coinminers and ransomware. Visiting these types of websites increases the risk of infection by two-fold.