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.
A study shows pigeons tackle complex problems using associative learning and error correction, similar to AI models. Researchers used an AI model to replicate the pigeons' behavior, finding strong evidence for the similarities between pigeon and AI learning mechanisms.
A new study published in eClinicalMedicine suggests that ECG-AI can flag some risks years sooner than current risk calculator equations by identifying signs of coronary artery disease, such as calcification and blockages. The technology has the potential to save more lives by identifying people who do not know they have coronary disease.
A new study suggests an artificial intelligence tool can detect distress in hospital workers' conversations with therapists during the pandemic. The tool analyzed digitalized session transcripts to identify common phrases tied to mental illness using natural language processing.
AI medical devices can improve diagnosis and treatment, but their accuracy and limitations must be carefully considered. Developers must ensure transparency about AI's performance and limitations to avoid harming patients and exacerbating health inequities.
Researchers at MIT found that similarity-focused generative AI models falter when tasked with designing new products, highlighting the need to prioritize innovation in engineering tasks. By adjusting training objectives and metrics, AI can be an effective 'co-pilot' for engineers, enabling faster creation of innovative products.
Researchers develop integrated photonic-electronic hardware capable of processing three-dimensional (3D) data, doubling parallelism for AI tasks and significantly boosting energy efficiency. The new chip can process 100 electrocardiogram signals simultaneously with high accuracy, outperforming electronic processors.
A global team of scientists emphasizes the need for collaboration between experts in AI, medicine, ethics, and beyond to develop fair models. They argue that focusing on equity rather than complete equality is a more reasonable approach, considering factors like race, gender, and patient preferences.
A new AI-powered tool, Salmon Vision, enables real-time monitoring of salmon populations in British Columbia and beyond, addressing data-poor fisheries and climate-smart management. The technology has shown promising accuracy in identifying salmon species and yields mean average precision rates of up to 90% for key fish species.
A new study by Klick Labs reveals that AI technology can screen for Type 2 diabetes using six to 10 seconds of a person's voice, with high accuracy rates. The research used acoustic features to analyze recordings from over 18,000 participants and identified significant vocal variations between individuals with and without the condition.
A new AI algorithm developed by Cedars-Sinai can detect atrial fibrillation in people without symptoms, improving stroke prevention. The algorithm was trained on over a million electrocardiogram readings and accurately predicted cases of atrial fibrillation within 31 days.
Researchers from KTU and partners propose a gamified learning approach to acquire knowledge in programming. The method creates a personalised learning process using AI or tutors to monitor progress and adapt goals accordingly.
Researchers used deep learning to identify dihydroartemisinin as a potential osteoporosis treatment that maintains mesenchymal stem cell stemness and produces more osteoblasts. The study found that administering DHA extract for six weeks significantly reduced bone loss in mice with induced osteoporosis.
A new AI tool provides fully automated, easy-to-use evaluation of brain tumors using amino acid PET scans. The deep learning-based segmentation algorithm assesses treatment response with quality comparable to that of an experienced physician.
The American College of Surgeons (ACS) Clinical Congress 2023 offers media credentials to cover groundbreaking research, connect with surgeon experts, and learn about the latest trends in surgery. Key topics include artificial intelligence, COVID-19's impact on cancer care, and pediatric trauma.
The High Performance Data Facility Hub will provide researchers with unprecedented data management resources, accelerating scientific discovery through seamless access to large and complex datasets. The hub will be led by Jefferson Lab and partner with Lawrence Berkeley National Laboratory.
Northwestern University engineers developed a nanoelectronic device that can perform accurate machine-learning classification tasks in real time with reduced power consumption. The device can be deployed directly in wearable electronics for real-time detection and data processing, enabling more rapid intervention for health emergencies.
Researchers from Mindgard and Lancaster University exposed vulnerabilities in major Large Language Models (LLMs) that can be copied for as little as $50. This 'model leeching' attack allows attackers to gain insights into how LLMs work, enabling them to launch targeted attacks with an increased success rate.
Researchers developed an AI-based method to estimate BMD from plain X-ray images using a hierarchical learning framework. The approach showed high performance and reliability in estimating BMD, with correlation coefficients of 0.88 and 0.92 compared to DXA and QCT.
The Digital Twin Brain platform combines intricate brain atlases and dynamic neural models to simulate human brain functions. This innovative approach holds promise for advancing artificial general intelligence and precision mental healthcare.
A new AI software has achieved a 100% detection rate for melanoma, significantly improving skin cancer detection accuracy. The software correctly identified 99.5% of all skin cancers and 92.5% of pre-cancerous lesions, with potential to reduce face-to-face consultations and enhance dermatology triage.
The author estimates that AI-related electricity consumption could increase by 85-134 TWh annually by 2027, comparable to the annual electricity consumption of countries like the Netherlands and Sweden. The growth highlights the need for mindful AI adoption to minimize energy-intensive applications.
A new generative model named scPoli enables multi-scale representations of cells and samples, facilitating the integration of high-quality large-scale datasets for novel biological insights and disease understanding. This model accelerates atlas building and usage, ultimately accelerating disease understanding and therapy development.
The study developed a highly accurate AI model for fully automated cancer detection, including small and difficult-to-detect tumors. The model could detect visually imperceptible cancer from normal-appearing pancreases substantially early before clinical diagnosis, with a median of 438 days.
A new AI tool developed by Brazilian researchers can detect potentially cancerous lung nodules in CT reports, missing a crucial early diagnosis. The NLP tool achieved an accuracy rate of 97% in identifying suspicious nodules.
Researchers developed AI tools to analyze speech patterns in people with schizophrenia and found that these patterns can be distinguished from those of healthy individuals. The study uses an AI language model trained on internet text to represent the meaning of words, and it was able to predict the words generated by control participan...
Researchers at BYU and Duke University found that AI can improve conversation quality and promote civil dialogue in online interactions. By using AI-generated rephrasings of users' messages, participants exhibited greater willingness to listen to opposing viewpoints and reported higher conversation quality.
Post-Acute Sequelae of COVID-19 research aims to track long-term health symptoms in survivors. A $3.7 million grant will support the development of self-supervised deep learning technologies to recognize post-COVID lung progression phenotypes.
A new generative AI model enhances clinical accuracy and textual quality of chest radiograph reports, surpassing traditional methods like teleradiology. Its implementation could enable timely alerts for life-threatening conditions, aiding imaging interpretation and documentation.
Researchers at the University of Texas at Austin developed an AI algorithm that accurately predicted 14 earthquakes within about 200 miles of their location and strength, with only one false warning. The system detected statistical bumps in real-time seismic data and paired them with previous earthquakes to make predictions.
Researchers developed a novel approach to predict therapeutic targets for aging and age-related diseases. They trained a domain-specific BioGPT model on biomedical literature, which improved its performance in identifying prospective targets.
A coordinated network of space lasers could prevent collisions with manned and unmanned space assets by nudging debris off potential collision courses. The artificial intelligence-powered lasers can maneuver and work together to respond rapidly to debris of any size.
Researchers at Argonne National Laboratory have developed an autonomous microscopy technique that uses AI to selectively target points of interest for scanning, speeding up the experimental process and allowing for greater efficiency in facilities with limited beam time. This innovative approach has the potential to accelerate scientif...
Researchers found that humans can inherit AI biases after interacting with a biased system, leading to a permanent negative impact on human decisions. This effect was observed in three experiments, where participants who were aided by a biased AI system continued to replicate its bias even when unaided.
Researchers from SUTD successfully applied reinforcement learning to a video game problem, creating complex movement designs that outperformed top human players. The study's findings have the potential to impact robotics and automation, ushering in a new era of movement design.
Researchers discovered that monk parakeets possess a unique tone of voice, known as a voice print, similar to humans. This finding raises the possibility that other vocally flexible species may also have a voice print.
Researchers from the University of Tokyo have developed an AI-powered drone system that analyzes young plants to predict their expected growth characteristics. By identifying optimal harvest times, farmers can reduce waste and improve their income by up to 20.4%, while also benefiting consumers and the environment.
A study of 33 physicians across 17 specialties found that chatbots provided largely accurate information to diverse medical queries. However, the chatbots had important limitations that require further research and model development.
Researchers discovered that users' prior beliefs about an AI chatbot's motives significantly impact their interactions with the agent. Priming users to believe certain things about the AI's empathy, neutrality, or manipulation influences their perception of its trustworthiness and effectiveness.
A new AI method leverages causal relationships in genome regulation to efficiently identify optimal genetic perturbations for cellular reprogramming. The technique reduces experimental costs by prioritizing the most informative interventions, leading to faster convergence and more effective results.
GlowTrack, a non-invasive movement tracking method using fluorescent dye markers, improves the capture of diverse movements in laboratories. This technique enables easier comparison of movement data between studies, increasing scientific discovery and advancing fields like biology, robotics, and medicine.
Researchers found that participants preferred 60-70 options from ChatGPT, citing high perceived accuracy and increased intent to purchase. This contradicts traditional choice overload theories, highlighting the impact of personalized recommendations on consumer decision-making.
The University of Trento coordinates a European research network, Elias, aiming to establish Europe as a leader in AI research. The project focuses on developing new computational systems and models for sustainable innovation, social cohesion, and reliable AI.
Researchers developed MonoXiver, a new method to help AI extract 3D information from 2D images, making cameras more useful tools for emerging technologies. The method significantly improves accuracy when used in conjunction with existing techniques, such as MonoCon.
Researchers identified potential therapeutic targets for Alzheimer's disease and other conditions using a new approach combining AI-driven target identification with protein phase separation analysis. The study provides insights into the role of protein phase separation in human disease and its potential as a therapeutic target.
Researchers at the University of Zurich developed PlantServation, a method that enables scientists to observe plants with great precision using AI and machine learning. The technique allows for the analysis of millions of images taken from various weather conditions, providing insights into how plants respond to environmental factors.
The Tong test proposes five critical characteristics for AGI benchmarks: infinite tasks, self-driven task generation, value alignment, causal understanding, and embodiment. This innovative approach combines a general algorithmic testing paradigm with human-AI interaction-based testing.
The UW team's system uses self-deploying microphones to divide rooms into speech zones and track the positions of individual speakers. The robots disperse as far from each other as possible, allowing for greater sound control and isolating specific areas or separating simultaneous conversations.
Scientists developed computational eye models to help patients and surgeons select ideal intraocular lenses and predict visual outcomes. The technology uses anatomical information of the patient's eye to provide guidance on expected optical quality post-operatively.
Researchers used AI to predict 3D shapes of over 215 million proteins, providing insights into their functions and evolution. The Protein Universe Atlas offers a valuable resource for scientists to explore protein diversity.
A comprehensive survey of ChatGPT papers reveals a rapid increase in interest for NLP models, but also raises concerns about biased content generation and technology misuse. The study emphasizes the need to establish responsible development and deployment frameworks for ChatGPT.
Researchers at U of A are developing an AI-powered system to analyze cardiac images, enabling clinicians to diagnose heart disease more accurately. The project aims to reduce healthcare costs and improve patient outcomes, with potential global implications.
A study funded by a $180,000 grant from the National Science Foundation will investigate sleep and sleep disorders using RFID tags attached to clothing. The research aims to detect abnormal body movements that may indicate health problems, such as falls in elderly individuals.
A new deep-learning model was developed by Professor Sanghyun Park's research team at DGIST to classify brain waves with high accuracy using only a small amount of data. This model is capable of overcoming the limitations of existing classification models and can be used for future research related to brain waves.
The project aims to assess the operational resilience of microgrids on DoD installations and ships, using new operational resilience indexes developed by Lehigh University researcher Javad Khazaei. The team will develop a dashboard to monitor resilience indexes in real-time, providing recommendations for improving the systems.
The Open Encyclopedia of Cognitive Science (OECS) is a dynamic web reference that will equip readers with essential tools to grapple with the profound implications of cognition and intelligence in today's society. With generous funding from James S. McDonnell Foundation and the Allen Institute for AI, the first set of articles will be ...
A group of experts has developed a framework to research and apply brain-cell-based computer technology responsibly. The technology has significant promise for accelerating disease understanding but raises questions about the moral status of bio-computers.
Researchers will develop new ecological models to analyze data from camera traps, satellite images, and DNA sequences to monitor biodiversity changes around the world. The project aims to detect early warnings of species moving north due to climate warming, providing insights into mechanisms of negative impacts on biodiversity.
A new UTHealth Houston study reveals that implementing artificial intelligence-powered software can significantly reduce treatment time for stroke patients undergoing endovascular thrombectomy, with an average reduction of 11 minutes in time to thrombectomy initiation.
A study published in Scientific Reports found that large language model AI chatbots can generate creative ideas at least as well as the average human in a divergent thinking task. However, human participants with the highest scores still outperformed the best chatbot responses, especially in categories such as fluency and flexibility.
Researchers found that even top-performing AI models can mistake nonsense sentences for natural language, highlighting the need for improvement. The study suggests that comparing human language processing to AI's could provide new perspectives on how we think.