Articles tagged with Artificial Intelligence
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
Industry and academic experts discuss the potential of new materials, configurations, and integration technologies to overcome bandwidth limitations and operational robustness issues in silicon photonic modulators. These advancements are expected to impact emerging applications such as data centers, AI, quantum information processing, ...
The In-Space Physical AI Workshop, held at Rice University's Ion District, brought together top scientists and experts to explore AI applications in space. Key findings included the potential of AI to streamline spacecraft navigation and crew health management.
Researchers have identified three distinct subtypes of Chiari type-1 malformations with distinct characteristics, enabling physicians to develop treatment protocols for patients. The study used artificial intelligence to analyze data from over 1,200 patients and identified patterns that can inform medical decision making.
Ayya Azzahra of CervivAI and Neda Razavi of iSono Health have been named as the two winners of Qatar Foundation's World Innovation Summit for Health (WISH) 2024 Innovation Competitions. The awards include cash prizes and mentoring sessions with leading industry experts.
A new approach using topological data analysis (TDA) enhances the reliability and reduces bias in AI systems used for medical diagnosis in radiology. TDA captures intricate features and provides a holistic view of medical images, leading to more accurate diagnoses and equitable patient care.
The NJIT team's Limelight Rainforest developed a drone-delivered technology capable of identifying thousands of rainforest species in mere hours. The device uses telemetry, satellite communications, and AI to interpret data from advanced microphones, cameras, and capture systems.
New algorithm CALDERA enables leaner LLMs with improved performance, reducing costs, energy consumption and privacy risks. This allows organizations to adapt models to their specific needs without sharing sensitive data, enhancing user privacy.
The NIH-developed AI algorithm, TrialGPT, can identify relevant clinical trials for eligible patients and provide a clear explanation of their eligibility. The researchers found that clinicians using TrialGPT spent 40% less time screening patients while maintaining the same level of accuracy.
The EDAI framework is a comprehensive guideline designed to embed equity, diversity, and inclusion (EDI) principles throughout the artificial intelligence (AI) lifecycle. It addresses a significant gap in current AI development and implementation practices in health and oral healthcare, ensuring AI systems are socially responsible and ...
Erdogan Kaya and his team aim to create an AI curriculum for grades 4-5, focusing on emergent multilingual learners and preparing students for AI-intensive careers. The project explores the impact of the integrated curriculum on students' understanding of AI concepts and teachers' AI teaching efficacy beliefs.
A new AI program, PanEcho, has been developed to interpret echocardiography videos independently, reducing wait times and improving timely medical care. The program demonstrated accuracy in estimating continuous echocardiographic parameters and quantifying left ventricle dimensions and function.
A new study reveals that an AI algorithm can accurately detect early-stage metabolic-associated steatotic liver disease (MASLD) in patients who meet the criteria, leaving 83% undiagnosed. This highlights the need for improved screening and diagnosis methods to prevent progression to advanced liver disease.
The NASA Goddard Lidar team has developed a system that can produce higher resolution data within a smaller space, significantly increasing efficiency compared to current models. This technology, known as CASALS, uses artificial intelligence and other technologies to allow the instrument to make its own decisions while in orbit.
Researchers found that membership inference attacks on large language models (LLMs) are not effective in measuring information exposure risks. The common method used to test LLM leaks suffers from ambiguity due to the fluidity of language, making it difficult to define a representative set of non-member candidates.
A panel of bioethicists and experts emphasize that human accountability is crucial for healthcare decisions made by AI. The importance of diverse data sets was also stressed to avoid biases in AI-enabled medical technologies. Experts stress the need for collective liability among developers, programmers, and data scientists.
Researchers at the University of Washington have developed a headphone prototype that can create 'sound bubbles' around the wearer, allowing them to focus on conversations without external noise. The system uses AI algorithms and machine learning to track sound sources and suppress distant noises.
Neuro-oncology experts developed guidelines to standardize AI use in brain cancer diagnosis and treatment. The recommendations aim to ensure reliable clinical trial results and protect patients.
The partnership aims to improve the speed and accuracy of flood damage assessments by combining multi-modal data sources and a novel vision language model. The system will enable first responders to quickly allocate resources and respond more efficiently to weather disasters.
Researchers developed an AI-powered model called FastGlioma that can detect residual tumor tissue with high accuracy in 10 seconds. The technology outperformed conventional methods, reducing the risk of missed tumors by nearly 75%. This innovation could change the field of neurosurgery and minimize reliance on radiographic imaging.
The joint Center for Health AI will focus on making care more personalized and effective while being more efficient and manageable for physicians. AI will be used to streamline workflows and administrative tasks, reducing burnout among healthcare workers and improving patient experience.
Researchers developed a new AI-powered diagnostic system, FastGlioma, which reveals invisible cancerous tissue in brain tumor surgery. The technique may delay or prevent recurrence of high-grade tumors and improve patient survival.
A new study published in JAMA Network Open found that using Chat GPT Plus does not significantly improve the accuracy of doctors' diagnoses, but it outperformed conventional methods in certain cases. The researchers suggest that physicians need more training and experience with AI to capitalize on its potential.
A study by Niigata University found that AI analysis of PET/CT images can predict the occurrence of interstitial lung disease, a serious side effect of immunotherapy. Patients with high inflammation in non-cancerous lungs are at a higher risk of developing this condition.
Researchers at Tufts University have discovered that AI's poor performance in conversational skills stems from its limited exposure to transcribed spoken language. The AI is trained on vast datasets of written content but lacks the nuance of human conversation, making it struggle with timing and turn-taking.
NeuroMechFly v2 simulates how a fruit fly navigates through its environment while reacting to sights, smells, and obstacles. The model can track moving objects visually or navigate towards an odor source, while avoiding obstacles in its path, enabling researchers to study brain-body coordination and animal intelligence.
The study emphasizes the need for a coherent approach to understanding A.I. threats, recognizing the intricate interplay between technology and society. Experts propose involving laypeople and experts in risk assessment processes, as well as promoting social resilience to ensure better decision-making.
The 12th Heidelberg Laureate Forum will bring together 200 talented young researchers from around the world to interact with renowned laureates of prestigious prizes. The event offers a unique opportunity for cross-generational scientific dialogue, networking, and collaboration.
A new system combining high-speed video and an AI algorithm can detect high blood pressure and Type 1 or Type 2 diabetes from subtle changes in blood flow, potentially leading to early detection and treatment. The technology is still in its preliminary stages but holds promise for non-invasive monitoring of health at home.
AI models trained on limited data may misdiagnose certain populations, particularly those in underserved communities. Researchers propose six key strategies to develop fair AI models, including using diverse datasets and transparent decision-making processes.
Researchers at Mass General Brigham developed an AI algorithm to identify long COVID cases in patients' health records, revealing a higher prevalence rate than previously thought. The tool uses 'precision phenotyping' to sift through individual records and track symptoms over time, reducing bias in diagnosis.
The University of Washington School of Medicine has released a flagship AI-ready dataset for a type 2 diabetes study, featuring a diverse range of participants and novel measures. The dataset includes environmental sensor data, survey responses, eye-imaging scans, and traditional biologic variables.
The new AI-based Natural Language to Query (NLQ) technology in Dimensions translates user intent into a structured Boolean query, ensuring consistency and transparency. This update enables users to save time while producing accurate results and previewing their search outcomes more efficiently.
Researchers trained an AI model on goat faces in pain, achieving 62-80% accuracy. This technology may help clinicians treat pain effectively in patients who cannot speak. The goal is to develop a more generalizable system for pain assessment in animals and eventually humans.
Researchers developed an innovative automated wildlife camera network to monitor species in a Dutch coastal dunes nature reserve. The system, which combines autonomous cameras, wireless data transmission and AI-driven species identification, has been shown to be cost-efficient and efficient, providing new insights into the habitat use ...
Research articles highlight the limitations of the 'tens rule' in invasion ecology, while also showcasing the growing use of crowdsourced science in environmental reviews. Additionally, a study uses artificial intelligence to identify individual animals with high accuracy, improving conservation strategies.
MIT researchers developed a theoretical foundation for methods to aggregate genes into related groups, enabling the efficient learning of underlying cause-and-effect relationships. They achieve this using only observational data, potentially paving the way for targeted treatments.
Researchers developed a software tool called Perseus that identifies critical tasks in AI training and slows down processors not on the path, eliminating unnecessary power use. This approach saves enough energy to power 1.1 million US homes in 2026 and reduces AI's carbon footprint.
A new crowdsourcing system, FireLoc, uses a network of low-cost mobile phones to detect wildfires minutes—even seconds—after they ignite. The system prioritizes privacy and accurately maps wilderness fires to within 180 feet of their origin.
Recent advancements in diagnostic techniques, including artificial intelligence integration, biomarker discoveries, and imaging technologies, have transformed the detection of pancreatic cancer. Key findings include improved sensitivity and accuracy of early-stage lesion identification using AI models, as well as the discovery of novel...
Researchers developed a multimodal dataset, TimelyTale, to gather passenger-specific sensor data for context-relevant explanations. The approach effectively identified the timing and frequency of passenger demands for explanations, enabling the creation of a machine-learning model to predict the best time for providing an explanation.
A recent study by Ruhr-University Bochum found that 0.052% of Twitter accounts use AI-generated profile pictures, which are often linked to fake profiles spreading disinformation and propaganda. The researchers also found that these accounts had fewer followers and were more likely to be blocked by Twitter.
Hoda Eldardiry receives $349,360 grant from NSF to develop practical competencies for students to apply ethical principles in AI system design. Her team aims to engage industry professionals to translate AI ethics into concrete decision-making.
The NSF-Simons AI Institute for the Sky (SkAI), led by Northwestern University, will develop innovative AI tools capable of handling vast data from astronomical surveys. Funded by a $20 million grant, Argonne National Laboratory will help drive this revolution in astronomy.
Researchers at Linköping University have developed a new version of AlphaFold that can predict the shape of very large and complex protein structures, integrating experimental data. This breakthrough aims to improve the development of new proteins for medical drugs.
Researchers found that AI tools can link genetic variations with diseases like diabetes without considering the complexity of genetics. A new statistical method can reduce false positives, but proxy information studies also introduce misleading correlations, warns Qiongshi Lu.
Researchers at NCSA have presented a novel post-quantum cryptography network instrument to measure PQC adoption rates and ensure secure data safeguarding. The project's findings indicate that only OpenSSH and Google Chrome have successfully implemented PQC, achieving an initial adoption rate of 0.029%.
The AI-powered system can detect toxic gases like nitrogen dioxide in real-time, identifying the source of harmful gas leaks. The system's optimization technique ensures fewer resources are used while providing faster and more accurate gas leak detection.
Researchers developed a new AI model, BiomedGPT, to support various biomedical tasks. The model achieved 16 state-of-the-art results in 9 biomedical tasks and demonstrated robust predictive abilities.
MIT researchers develop 3D transistors using quantum mechanical properties to achieve low-voltage operation and high performance. The devices can deliver comparable performance to state-of-the-art silicon transistors while operating efficiently at much lower voltages.
A new study calls for the adoption of new research ethics policies to foster learning and discussion of ethical issues. The guidelines aim to shift from compliance-based ethics to promoting ethical norms and practices.
A team of computer scientists has developed an interactive AI tool that transforms static physics textbook diagrams into 3D simulations, allowing students to visualize complex concepts like momentum and electrical currents in action.
A new generative AI tool called Theseus is being developed to reduce time and labor in computational modeling, suggesting and running simulations to accelerate research and discovery. The AI assistant aims to enhance the work of computational scientists by providing scientific intuition, checking code for bugs and making suggestions.
A new reinforcement learning framework, AVATARS, uses diverse sensor streams to track whales and predict their surface locations. The framework aims to minimize missed encounters and improve data collection for Project CETI.
Researchers developed a wearable ultrasound device that tracks muscle function without invasive procedures, offering high-resolution imaging and wireless monitoring capabilities. The technology has potential applications in respiratory health and human-machine interfaces.
Two teams, led by Rice's ENRICH office, have won $100,000 in matching funds from partnering institutions to investigate AI-based symptom checkers and electrocardiogram data for improving cardiovascular risk assessment. The projects aim to mitigate vulnerabilities and reduce health disparities.
Researchers synthesizing AI with biomarker analysis aim to detect early signs of aging and enable targeted interventions to delay disease. This approach has the potential to slow, prevent or reverse certain effects of aging.
Researchers found that AI doctors who recall patients' social information, with privacy control offered, increase patient satisfaction. Human doctors don't require social or medical information to establish a close relationship with patients.
A new University of Illinois study examines the adoption of robotic weeding technology to fight superweeds, finding that forward-looking management strategies are more effective than myopic approaches. The research suggests that farmers with a long-term perspective on weed resistance will benefit from early adoption of robots.
Yihao Zheng and his team are developing a fiber-optic probe that analyzes artery blockages in the brain and guides procedures for blockage removal. The technology uses light and advanced calculations to determine the properties of blood clots, enabling doctors to make informed decisions about how to remove them.
Researchers developed an AI-based method to analyze kidney lesions in female patients with Alport syndrome, predicting renal prognosis and guiding treatment interventions. The approach uses a modified stain and deep learning to detect basement membrane lesions, showing a positive correlation with proteinuria concentration.