Articles tagged with Artificial Intelligence
Researchers developed an AI model powered by deep learning algorithms that outperforms traditional dynamic models in predicting central Pacific El Nino events. The study sheds light on the potential of AI to enhance seasonal forecasts, offering significant advancements in climate prediction.
A new editorial explores the potential of machine learning to enhance early cancer detection in primary care, leveraging extensive patient data and improving risk stratification accuracy. The authors emphasize the need for responsible implementation, collaboration, and validation across diverse populations.
Researchers identified 145 key genetic points controlling skeletal proportions using AI on tens of thousands of X-ray images and genetic sequences. This discovery opens a window into predicting patients' risks of developing conditions like back pain or arthritis.
The use of AI models in healthcare for ethnic minority populations may worsen existing inequalities if not addressed. The researchers argue that the lack of diverse representation in research trials and data can lead to ineffective treatments and guidelines.
Researchers developed a tool called SKILL that enables AI agents to learn 102 distinct tasks by sharing knowledge in parallel, reducing the time needed to master new skills. The technology has potential applications in medicine, education, and other fields where vast knowledge is required.
Scientists will use AI-powered monitoring stations to track species populations and assess the effectiveness of agri-environment schemes in improving biodiversity. The study aims to demonstrate how different farming systems and practices affect species populations, providing crucial evidence for sustainable land management policies.
The study evaluates recent research on artificial intelligence-generated molecular structures from the perspective of medicinal chemists, recommending guidelines for assessing novelty and validity. Insilico Medicine's recommendations aim to improve the process of generating and evaluating novel AI-generated drugs.
In a post-truth era, Americans tend to trust information sources with good intentions over those with malicious intent. When presented with claims of fact, participants classified them as true more often if the source was trying to provide an approximate account rather than a precise one.
A study comparing history of present illness summaries generated by a chatbot and senior internal medicine residents found that both were graded similarly by internal medicine attending physicians. The findings suggest the potential of chatbots to aid clinicians with medical documentation, highlighting their accuracy.
A new study by NYU Tandon School of Engineering and Grossman School of Medicine reveals that chatbots' responses to people's healthcare-related queries are nearly indistinguishable from those provided by humans. Participants were able to correctly identify human-generated responses only 65.1% of the time, while chatbot responses were a...
Researchers from Edith Cowan University developed software to analyze bone density scans, detecting abdominal aortic calcification (AAC) at high accuracy. The AI can predict cardiovascular disease events and late-life dementia, allowing for early interventions.
Researchers at the University of Zurich have used AI to uncover the underlying cellular mechanism behind kidney disease in cystinosis. They identified a causal association between mTORC1 protein regulation and the disease, highlighting a promising therapeutic target.
Researchers create a new privacy metric, Probably Approximately Correct (PAC) Privacy, that enables the addition of minimal noise to protect sensitive data. The algorithm automatically determines the optimal amount of noise needed without requiring knowledge of the inner workings of the model or training process.
Recent AI advancements in healthcare and animal behavior pose unique ethical concerns and policy challenges. Meanwhile, generative AI technologies raise questions about copyright and training data, while task automation via AI innovations could reduce income inequality. These pieces explore the benefits and risks of machine intelligence.
Lero is recruiting 16 top international post-doctoral researchers for a €2.9 million fellowship program focusing on privacy, trust, inclusion and fairness in software expertise. The program will provide discipline-specific skills training and enhance career development.
A new study by MIT researchers finds that China's government uses AI-driven facial recognition to suppress dissent, but this approach also spurs the development of better AI tools and other innovative technologies. The study suggests that this 'AI-tocracy' cycle entrenches the regime while stimulating further innovation.
A new report suggests that AI-powered robot companions could alleviate the loneliness epidemic and its associated health risks. Companion robots have already shown promise in reducing stress and promoting physical and mental well-being in socially isolated older adults.
The University of Surrey is involved in six national energy research centres, focusing on sustainable solutions for a greener future. Academics are developing hydrogen and ammonia as alternative fuels and boosting bioenergy production to reduce the UK's energy demand.
A new AI-powered NLP model developed by Emory and Georgia Tech successfully triaged patient messages reporting positive COVID-19 test results with 94% accuracy. The model expedited physician-patient communication, leading to faster access to treatment within a five-day window.
Researchers examine whether robots and AI can replicate the ethical concepts attributed to human nurses, including advocacy, accountability, cooperation, and caring. While AI can inform patients about medical errors and present treatment options, it questions its ability to truly understand and empathize with patients' values.
Researchers found that popular GPT detectors misclassify articles written by non-native English speakers as AI-generated. The study suggests using these detectors with caution and calls for enhancements to address biases. This could have significant implications for students, job applications, and search engines.
Researchers developed an AI model that accurately classifies six types of valvular heart disease using chest radiographs, with high accuracy rates. The model's potential applications include supplementing echocardiography in areas where specialists are scarce and improving emergency care.
The University of Houston's CYBER-CARE research center aims to prevent cyberattacks that could compromise the safe movement of people and goods in the US. The center will focus on four goals, including exploring advanced theories to mitigate the impact of large-scale cyberattacks.
A new study found that deepfake video clips prompted false memories of films in 49% of participants, comparable to text descriptions. Many participants reported remembering the fake remakes as better than originals, highlighting concerns over artistic integrity and shared social experiences.
Researchers demonstrate that AI language models like ChatGPT can generate high-quality fraudulent medical articles with standard sections and references. The study highlights the need for increased vigilance and enhanced detection methods to combat potential misuse of AI in scientific research.
A new study from the University of Montana found that ChatGPT's GPT-4 AI has reached the top 1% in terms of original creative thinking, outperforming human students and national averages. The AI excelled in generating fresh responses, a hallmark of human imagination.
The study reveals five distinct brain types, each suited for its purpose, from a jellyfish's diffuse neural network to the human brain's reflective capabilities. Researchers suggest that autonomous machines can learn from coordination in bees, rapid thinking in birds, and single-mindedness in worms.
Developing a technique to create conductive polymer wire connections between electrodes enables artificial neural networks that overcome the limits of traditional computer hardware. The approach allows researchers to control and train the network using small voltage pulses.
Only 36% of UK employers have invested in AI-enabled technologies like industrial robots and chatbots over the past five years, new research suggests. The survey highlights a growing skills problem, with less than 10% anticipating digital skills training investment in the coming years.
A new method developed by the Max Planck Institute of Animal Behavior has counted Africa's largest bat colony using GoPro cameras and artificial intelligence. The estimate puts the colony at between 750,000 and 1,000,000 bats, making it the largest for bats by biomass anywhere in the world.
A new study by researchers at NYU and the New York Genome Center combines deep learning with CRISPR screens to control human gene expression. The model predicts on- and off-target activity of RNA-targeting CRISPRs, enabling precise gene controls for developing new therapies.
A new study published in NEJM Evidence validates a predictive AI biomarker for androgen deprivation therapy (ADT) benefit in prostate cancer. The study found that personalized use of short-term ADT could improve patient outcomes in men with predominantly intermediate-risk prostate cancer.
A new AI tool, MAFDA, tracks individual fruit flies' complex behaviors and compares them with their genetic backgrounds. This enables researchers to study behavior genetics and gain insights into inherited traits.
Researchers summarize existing compiler technologies in deep learning co-design and propose a new framework, the Buddy Compiler, to address performance bottlenecks in current AI applications. The study highlights the importance of hardware-software co-design in achieving optimal efficiency and effectiveness in deep learning systems.
A new machine learning model developed by University of Pittsburgh researchers uses electrocardiogram (ECG) readings to diagnose and classify heart attacks faster and more accurately than current approaches. The model improves risk assessment, helping patients receive appropriate care without delay.
Engineers at Rice University and the University of Maryland developed NeuWS, a technology that can undo light scattering effects, enabling full-motion video through various media. The technology measures wavefronts to rapidly decipher phase information, overcoming the 'holy grail problem' in optical imaging.
A team of researchers created a deep learning system capable of detecting natural disasters using images from Twitter and Flickr. The system, trained on over 1.7 million photographs, was able to accurately identify incidents such as floods, tornadoes, and forest fires.
The study uses AI-assisted methods to discover novel deaminase proteins with unique functions through structural prediction and classification, expanding the utility of base editors. New DNA base editors with remarkable features were developed, enabling tailor-made applications for various breeding efforts.
Researchers developed AEGIS, the first technique to detect backdoor attacks in robust machine learning models. It improves the trustworthiness of artificial intelligence by analyzing robust models and detecting mixed input distributions for poisoned classes.
A new AI tool can identify sperm in severely infertile men in seconds, compared to the hours it takes scientists. The algorithm improves antiquated approaches and increases the chance of a couple conceiving their own biological children while reducing stress on sperm and increasing efficiency.
A study published in Radiology found that AI algorithms with high diagnostic accuracy improved radiologists' detection of lung cancers on chest X-rays. High-accuracy AI led to more frequent changes in reader determinations, suggesting increased human trust in AI.
The VIS+AI framework enables seamless communication between human intelligence and artificial intelligence in visual analysis. It incorporates three iterative loops: interaction, execution, and intelligence optimization, allowing AI to adapt to dynamic data analysis processes guided by humans.
A new AI model has been developed to help doctors determine the extent of cancer within the prostate gland, improving the effectiveness of focal therapy. The model was found to be more accurate than magnetic resonance imaging (MRI) in predicting tumor margins, reducing the chance of cancer recurrence.
Researchers found that ChatGPT 4 can accurately identify appropriate imaging services for breast cancer screening and breast pain. The AI model outperformed its predecessor, ChatGPT 3.5, in providing evidence-backed guidelines for radiologists.
A new checklist has been proposed to reduce bias in AI algorithms, promoting more accurate and fair decision-making. The checklist provides a standardized framework for identifying and addressing biases in AI systems.
A research team at the University of Tsukuba has developed a secure AI technology that allows for the shared analysis of personal and identifiable data from multiple organizations. This will enhance the accuracy of AI analysis, particularly in disease prediction and educational effectiveness.
Research highlights how generative AI models encode biases and negative stereotypes in their users, particularly marginalised groups. This can lead to the mass generation and spread of nonsensical information, influencing human beliefs and perpetuating existing inequalities.
An AI model called SCORE-AI achieved human expert level performance in fully automated electroencephalogram interpretation. This technology has the potential to improve diagnosis and patient care in underserved areas and increase efficiency in specialized epilepsy centers.
Researchers developed Precious1GPT, a multimodal transformer-based approach for aging clock development and feature importance analysis. The model utilizes methylation and transcriptomic data to predict biological age and identify disease-related genes, providing a pathway for therapeutic drug discovery.
Researchers applied machine learning to brain responses and achieved near-perfect classification accuracy for songs that may become hits. The approach, called 'neuroforecasting,' uses data from a small group of people to predict population-level effects without needing to measure the brain activity of hundreds of people.
Researchers created a robot inspired by pangolins' ability to curl up into a ball, with a soft layer and hard metal components. The robot can emit heat when needed and transport particles like medicines, making it promising for minimally invasive medical procedures.
A communication robot is being developed to prevent elderly isolation by facilitating self-disclosure through different communication options. The study found that the most appropriate option depends on the recipient, message content, and sender's gender and personality traits, reducing participants' anxiety in self-disclosure.
Researchers have developed DyLiN and CoDyLiN, methods that handle non-rigid deformations and topological changes in 3D structure representation. These advancements enable real-time volumetric rendering and animation with improved visual fidelity and speed.
Generative AI raises fundamental questions about the creative process and human's role in it. Researchers highlight gaps in understanding perceptions of AI-generated content, ownership, credit, labor economics, and media ecosystem impact.
Researchers at Beth Israel Deaconess Medical Center used a generative AI chatbot to solve complex diagnostic cases, finding it accurate in nearly 40% of cases and providing correct diagnoses in two-thirds of challenging scenarios. The study suggests generative AI has the potential to assist medical professionals in diagnosis.
A new research project at University of Leicester will develop a digital 'twin' of the UK using artificial intelligence and big data to inform environmentally-friendly land use. The project aims to reduce emissions from cattle and sheep farming, which contribute around 10% of the UK's emissions.
A new AI-based technique measures brain fluid flow with unprecedented accuracy, revealing pressures and three-dimensional flow rates. This breakthrough could lead to the development of new treatments for Alzheimer's, small vessel disease, strokes, and traumatic brain injuries.
Research by Francis de Véricourt and Huseyin Gurkan found that trust in machines' decision-making ability is key to effective learning. They discovered that biased learning occurs when humans override algorithmic decisions without observing the machine's correctness, leading to incorrect usage of machines in decision making.
A machine-learning study has found that individual characteristics, including age and weight, determine which drug combinations most effectively reduce COVID-19 recurrence rates. The study used real-world data from a hospital in China and identified unique treatment combinations for different demographic groups.
Lero is recruiting 16 world-class researchers to work on privacy, trust and inclusion in software development through the €2.9 million SyMeCo programme. The programme will attract outstanding international candidates from computer science and related fields.