Research on making sense of scientific and medical data. Covers AI error-correction, single-cell search engines, optical computing, and measurement reliability.
A $5 million NSF grant is powering AI innovations in Pegasus, a widely used workflow management network. Researchers aim to develop intelligent workflow management tools that adapt to evolving user needs and dynamic resource conditions.
A recent study by the University of Washington reveals that highly walkable areas lead to significantly increased walking among residents. The study used data from the Argus step-tracking app and found that a 49-point increase in Walk Score was associated with an average increase of 1,100 steps per day.
Adults with long COVID experience worse work impairment, missed work, and financial distress compared to those without long COVID. Vaccination is associated with improved work outcomes and reduced financial distress among individuals with long COVID.
The Intelligent Data Exploring Assistant (IDEA) framework combines large language models with scientific data to analyze complex geoscience data. Researchers can ask IDEA to retrieve data, run analyses, and generate plots using plain-language questions.
A recent study analyzed use of online asynchronous telemedicine abortion services from July 2023 to September 2024. The research found that these services increased access to abortion care, particularly in rural areas where traditional abortion providers are scarce.
A cross-sectional study found that white populations use more prescription drugs than Asian or Pacific Islander and Hispanic populations. After adjusting for age and disease prevalence, Black populations have lower prescription fill rates compared to the overall population average.
A new study uncovers coordinated efforts of paper mills, brokers, and infiltrated journals to fabricate research, pay for authorships, and citations. Millions of dollars are involved in these processes, with the problem so widespread that it's outpacing legitimate scientific publications.
A research team developed an innovative unsupervised model for industrial anomaly detection using paired well-lit and low-light images. The model leverages feature maps, Low-pass Feature Enhancement, and Illumination-aware Feature Enhancement to detect anomalies while remaining lightweight and memory-efficient.
A study using anonymized patient records from UC health centers found over 600 correlations between endometriosis and other conditions, including infertility, autoimmune disease, and certain cancers. The research supports the growing understanding of endometriosis as a multi-system disorder.
The FDA has authorized artificial intelligence devices for Alzheimer's and related dementias despite limited demographic data. Disease status, age, sex, and race were reported for fewer than half of devices, raising concerns about real-world generalizability.
A USC research team has made a groundbreaking discovery about the human spinal cord's role in bladder control. The study used functional ultrasound imaging to observe real-time changes in blood flow dynamics during bladder filling and emptying, revealing areas where activity is correlated with bladder pressure.
Answer ALS is launching a groundbreaking collaboration with Tulane University and the Pennington Biomedical Research Center to harness AI for ALS treatment discovery. The Louisiana AI Drug Development Infrastructure for ALS (LADDIA) will prioritize therapeutic targets using AI-driven insights from the Answer ALS' Neuromine Data Portal.
Researchers from Sapiens Labs created two ongoing data acquisition programs in India and Tanzania to collect large-scale, high-quality neuroimaging data. The programs have collected data from over 7,900 participants with comparable data quality to lab settings and lower costs.
The joint policy brief from four EU projects aims to guide successful implementation of the Green Deal Data Space. It recommends standardised data exchange technologies, inclusive governance frameworks, and metadata management to unlock Europe's full potential in environmental data.
A recent study published in JAMA Otolaryngology–Head & Neck Surgery found an association between cannabis use disorder and benign salivary gland tumors. The researchers call for further prospective research to confirm this association and understand the relationship between cannabis use and these tumors.
Researchers used generative AI models like ChatGPT and DALL-E to analyze men's fashion trends and create realistic fashion collection images. The study highlights the importance of expertly worded prompts for accurate fashion design implementation, enabling efficient and creative use of generative AI in fashion.
A recent study found that people in poorer areas receive three times the prescriptions for opioids than those in wealthier areas, despite a decline in overall opioid use in Canada. The research highlights the persistence of inequalities in healthcare and the need for targeted interventions to mitigate the risks of opioid misuse.
The new compute roadmap aims to improve lives and livelihoods with advanced computing power. It includes investments in AI research, healthcare diagnostics, and renewable energy.
A new study by Bar-Ilan University finds that most Amazon Mechanical Turk participants produce highly inconsistent responses, even among high-performing users. In contrast, elite Master workers consistently provide high-quality data, recommending their use for future research to ensure reliable empirical science.
Researchers at Notre Dame's School of Architecture and the Lucy Family Institute for Data & Society developed EcoSphere, an AI-powered platform that visualizes embodied carbon emissions. The tool helps city planners identify strategies to reduce carbon emissions through renovation and extended building life.
Pusan National University researchers developed a comprehensive issue set for MDA implementation, covering technical, organizational, and environmental challenges. The framework helps manufacturers prioritize issues and address them proactively, enabling efficient and effective data-driven smart manufacturing.
A study using AI language models analyzed sentiments and emotions expressed by almost 400 pediatric patients on social media, finding that 94% of comments were negative, with sadness and fear prevalent. The study highlights the need for integrated care approaches to support vulnerable young patients managing complex medical conditions.
Researchers develop a groundbreaking, non-destructive method to monitor oyster health by analyzing heartbeat patterns using high-resolution image processing. The technique tracks vitality loss through cardiac activity and biochemical markers, providing a sensitive and real-time tool for seafood quality assurance.
Life expectancy in California remained lower in 2024 than in 2019, with COVID-19 accounting for a deficit of 12.8%. The gap between racial groups narrowed, but life expectancy in the Black population was still significantly lower than others.
Researchers identified four distinct groups of autism linked to specific genetic variants and biological processes. The study's person-centered approach analyzing phenotypic and genotypic data from SPARK enabled more precise diagnoses and personalized support.
Researchers identified four distinct pathways leading to Alzheimer's disease, revealing how conditions progress step-by-step toward the condition. The study validated findings in a nationally diverse population, suggesting that understanding these pathways could fundamentally change how clinicians approach early detection and prevention.
Scientists have developed a new tool named scICE to tackle the stability problem in single-cell RNA sequencing data. The tool provides a way to validate clustering outcomes mathematically, ensuring higher confidence in conclusions drawn from single-cell data.
Researchers developed a non-invasive method combining 3D laser scanning and sensor data analysis to detect subsurface structural defects in water treatment filters. This breakthrough significantly reduces inspection time and labor costs, ensuring safer and more efficient water processing.
BingoCGN accelerates real-time large-scale graph neural network inference through cross-partition message quantization and a novel training algorithm, achieving up to 65-fold speedup and 107-fold increase in energy efficiency compared to state-of-the-art accelerators.
This cross-sectional study reveals a substantial rise in alcohol-associated liver disease mortality, particularly among women and younger adults. The findings highlight the importance of targeted public health initiatives to address this growing health concern.
A team of researchers developed a novel method called Time-Lagged Recurrence (TLR) to estimate the predictability of complex dynamical systems. TLR uses data-driven approach to evaluate how an ensemble of similar initial states evolves over time, determining local predictability at that state.
Cessation of public water fluoridation would lead to higher rates of tooth decay and increased healthcare costs in the US. The model suggests that current safe levels of fluoride have substantial ongoing benefits.
Researchers used anonymized GPS data from smartphones to monitor how wildlife reacts to people, highlighting the potential of human mobility data in tracking human-wildlife conflicts. The study's findings can inform conservation planning, help protect animals and wild spaces, and ensure that recreational activities are done responsibly.
The foundation recognizes five early-career scientists who apply computational methods to cancer research, with a focus on developing new protein designs and understanding chromatin modifications. Their work aims to improve treatment strategies and precision oncology for various cancers.
A new study applies network analysis to large-scale data from the French labor market, identifying four main clusters: diffusers, channels, hubs, and condensers. Diffuser occupations offer wide exit opportunities but are hard to enter, while channels and hubs face accessibility issues.
Researchers have developed CaliAli, an advanced analytical framework that aligns calcium imaging data across multiple sessions, allowing for the continuous tracking of individual neurons. This breakthrough enables long-term brain activity studies and advances understanding of memory formation, retention, and neurological diseases.
University of Missouri researchers create digital sentiment map using AI to analyze public Instagram posts, linking emotional tone to real-life features. The tool aims to improve city services, identify areas of concern, and inform emergency response decisions.
A new open-source tool, greenfeedr, is introduced to simplify the process of analyzing GreenFeed data from livestock. The R package offers functions for downloading, processing, and generating reports, allowing researchers and producers to automate routine tasks and gain insights into methane and carbon dioxide emissions.
A national survey found that 11.0% of adults reported using illicit opioids within the past year, with even higher rates of fentanyl use, indicating a pressing need for improved data collection efforts to inform policy and intervention strategies.
A study published in JAMA Neurology found no evidence supporting a diagnosis of the New Brunswick neurological syndrome of unknown cause, highlighting the need for independent clinical evaluations. The data revealed presence of several neurodegenerative and non-neurodegenerative conditions instead
A study of three national cohorts reveals increased abortion use among LGBTQ+ individuals, highlighting the need for tailored support. The findings suggest that these groups are disproportionately impacted by narrowing abortion access in the US after the Dobbs decision.
A new review advocates for building confidence in AI applications by implementing robust data governance frameworks, enhancing transparency, and involving stakeholders. The authors emphasize the importance of addressing ethical implications and ensuring equitable access to AI-driven innovations in clinical oncology.
A study analyzed per capita municipal expenditures and their correlation with population changes in small and medium-sized cities in Japan. The results revealed that prioritizing child welfare expenditures is a key strategy to sustain populations, while city planning expenditures on street maintenance and construction were also effective.
A new study reveals that China's sell-by-plan mandate, aimed at preventing insider trading, has failed to stop executives from profiting from private information. Executives have found a way to plan their sales far in advance, allowing them to cash out before bad news breaks, undermining market fairness and eroding investor trust.
A team of researchers at POSTECH has identified a hidden mechanism in Electrochemical Random-Access Memory (ECRAM) technology, enabling faster and more efficient AI computations. This breakthrough could lead to significant improvements in data processing and reduced energy consumption.
Researchers develop a new approach to automatically guide large language models (LLMs) towards generating accurate, properly structured outputs for various programming languages and formats. This probabilistic approach boosts computational efficiency, enabling small LLMs to outperform larger models in generating accurate code.
Research from Rutgers Health finds that children exposed to paternal depression at kindergarten entry are more likely to have behavioral difficulties and poor social skills at age 9. Fathers' mental health is crucial in supporting their children's development, and early intervention can help improve well-being for both parents and kids.
Researchers analyzed driving behavior data from Chinese electric vehicle drivers and found that rapid acceleration significantly impacts energy efficiency. The study provides actionable guidance for EV owners to improve their eco-driving behaviors and offers insights into developing personalized feedback systems.
Researchers developed a new framework, PAC Privacy, to maintain AI model accuracy and ensure sensitive data remains safe from attackers. The new variant of PAC Privacy estimates anisotropic noise, reducing computational cost and boosting accuracy.
Researchers developed a novel approach to visualize and analyze driving behaviors in electric vehicles, revealing the impact of driving patterns on energy consumption. Key findings show that rapid acceleration is a primary cause of excessive energy consumption, which can be mitigated by adopting eco-driving behaviors.
A study by Associate Professor Mitsuko Tanaka found that a good group work environment significantly increases motivation among English language learners, regardless of individual factors. The research suggests that educators should prioritize environmental preparation for successful project-based learning outcomes.
Researchers will use sensors and software to predict AM part lifespan, enabling cost savings and extending part life. The project aims to improve Darwin software to provide detailed insights into manufacturing processes.
A recent study published in Nature reveals a causal connection between the shingles vaccine and reduced risk of dementia. The analysis of data from a regression discontinuity design found a 20% reduction in dementia diagnosis risk among vaccinated individuals born on or after September 2, 1933.
A new study published in JAMA Network Open reveals a strong association between increased utilization of overtime and agency nurses and patient safety. The research found that prolonged exposure to high-stress work environments contributes to a higher incidence of pressure ulcers among patients.
The CONCERTO Project aims to advance the understanding and modelling of the terrestrial carbon cycle, reducing uncertainty in climate predictions. By integrating Earth observation data and innovative models, the project will contribute to improved climate policy and global efforts towards carbon neutrality.
A new study suggests AI-driven smart devices can revolutionize healthcare by detecting cardiac issues early, triggering emergency responses. The Internet of Medical Things (IoMT) technology enables real-time patient monitoring and analysis, improving efficiency and reducing costs.
A centralized notification pathway increased hypertension treatment in individuals with left ventricular hypertrophy. This study highlights the potential of leveraging underutilized cardiovascular data to enhance healthcare delivery.
Despite a rise in long distance running participation, cardiac arrests during US marathons and half-marathons have shown no significant increase, indicating improved emergency response measures are at play.
Anna Seigal, assistant professor at Harvard's John A. Paulson School of Engineering and Applied Sciences, has received the 2025 Sloan Research Fellowship for her work on connecting geometric invariant theory and maximum likelihood estimation in data science.
Scientists have identified COVID-derived molecular mimics that trigger autoimmunity, with some associated with type 1 diabetes and multiple sclerosis. The study suggests people with specific genetics may be at higher risk of COVID-induced autoimmunity.