Articles tagged with Data Analysis
The American College of Cardiology's Global Quality Solutions program now allows international hospitals to use approved internal data to meet accreditation requirements. This update enables hospitals to internally collect and submit aggregated data directly into ACC Accreditation tools, streamlining the accreditation process.
A recent study published in JAMA Internal Medicine found that oral semaglutide has a potential benefit in reducing heart failure events among people with type 2 diabetes and existing heart failure. The data support the use of oral semaglutide as a treatment option for these patients.
A new method called Distributed Cross-Channel Hierarchical Aggregation (D-CHAG) accelerates analysis of hyperspectral data, enabling faster AI-guided discoveries for high-performing crops. The approach reduces computational bottleneck and increases efficiency, making it possible to extract subtle patterns in plant physiology.
A cross-sectional analysis of nationwide population data reveals that high-deductible health plans are associated with worse overall and cancer-specific survival among cancer survivors. The study suggests that financial disincentives for medical care may lead to delayed or foregone necessary care, ultimately worsening cancer outcomes.
The study analyzed US state-level adult obesity prevalence from 1990 to 2022, showing a significant increase to 42.5% by 2022 and forecasted to 46.9% by 2035. Disparities in obesity rates vary substantially by race and ethnicity.
The University of Virginia has launched a cross-Grounds initiative to advance health and healthcare through data and artificial intelligence. The Collaboratory aims to accelerate discovery, share expertise, and lower collaboration barriers across disciplines.
The journal has been recognized for its significant international citations, with over 3 million documented in the past year. Its editorial leadership and publishing model ensure rigorous peer review and a multidisciplinary perspective, supporting high-quality research on AI and clinical applications.
Researchers used machine learning to identify conflict labels from data, discovering three archetypes with distinct geographic, demographic, and economic properties. The study emphasizes the limitations of existing conflict classifications and suggests new approaches for predicting conflict severity.
Researchers developed AI-powered in silico labeling to analyze cell images without staining, preserving cell health. The system leverages context, such as cell shape and position, to accurately stain rare processes like cell division.
A chemist proposes a framework for shared model proteins to improve reproducibility and coordination in protein science. The proposal includes five widely used proteins and aims to establish minimal reporting requirements and curated reference datasets.
This study reveals an increase in nonmedical childhood vaccination exemptions from 2010 to 2024, driven by the COVID-19 pandemic, with wide regional disparities.
A study by Bielefeld University used anonymized WhatsApp metadata to show that personalized feedback can help people understand their communication habits. Many participants adjusted their views on response speed and chat participation after seeing data-based visualizations.
Researchers found science fiction and genre elements were popular among readers, with top authors including Ursula K. Le Guin and Octavia E. Butler. The analysis also revealed trends driven by news events and the selection of canonical authors for the Seattle Reads program.
A simulation study forecasted potential injury reductions in the US with AV adoption, suggesting a possible decrease in road traffic injuries. However, predicted confidence intervals remain broad, and no scenario reduced injuries outside of these bounds.
In a prespecified exploratory analysis of the SELECT randomized clinical trial, semaglutide demonstrated significant reductions in hospital admissions and overall time spent in hospital. This finding suggests that semaglutide has broader health benefits for patients with obesity and established cardiovascular disease.
The study found a significant increase in alcohol-related hospitalizations between 2016 and 2022, with rising mortality rates and extended lengths of stay. Preventive efforts are needed to reduce population-level alcohol consumption and improve treatment outcomes for individuals with alcohol use disorder.
The study analyzed 785,881 total posts from 513 members of the 117th Congress, identifying 12,274 gun-related posts using keyword-based filtering. Democrats respond directly to shooting events within 48 hours, while Republicans show no such response.
Researchers developed G2PDeep, a web-based platform integrating six molecular data types to predict complex health outcomes. The platform enables better identification of omics-based molecular markers and improves personalized treatment strategies.
Researchers have launched a new multimodal medical dataset, Observer, capturing anonymized, real-time interactions between patients and clinicians. The dataset links video, audio, transcripts, and electronic health records to study subtleties like body language and environmental factors affecting care.
Studies show that patients with advanced ovarian and metastatic breast cancer dedicate approximately 7 hours per week to cancer-related tasks. Most participants report performing these tasks daily, impacting their time burden. The use of a mobile app facilitated the collection of detailed time-use data.
A study analyzed large-scale human ChIP-seq data to identify unmeasured transcription factor-tissue/cell type pairs, revealing significant gaps in current knowledge. These findings indicate that essential regulatory mechanisms may have been overlooked, emphasizing the need for strategic prioritization of measurement targets.
A new study reveals that Normalized Mutual Information (NMI), a widely used metric for algorithm performance, can produce biased results. The researchers developed an asymmetric, reduced version of the mutual information metric to eliminate biases and improve comparison across fields.
Researchers at UT Health Sciences Center have developed an AI-enhanced platform called ENRICH, which leverages advanced analytics with community-based human support to reduce treatment interruptions and improve cancer outcomes. The program identifies patients at highest risk for interruption and deploys targeted support resources.
A new study found that highly educated, Western European millennials have the most digital concerns, with individuals having higher levels of digital literacy being the most affected. The research also found that people's perceptions of digital harm are heightened by their level of digital exposure and knowledge.
A comprehensive analysis of 383 US cities found common patterns of isolation and segregation, with wealthy suburban areas and poorer downtown zones often having limited interactions between residents. Researchers recommend zoning incentives and strategic development to encourage greater diversity and social mixing.
A new study maps three decades of income inequality data globally, revealing worsening trends for half the world's population but 'bright spots' in regions with effective policies. Regional efforts such as investments in public health and education in India and cash transfer programs in Brazil show promise in reducing inequality.
Exposure to single and mixtures of perfluoroalkyl substances (PFAS) was associated with higher odds of endocrine disruption (ED) among women. Certain PFAS compounds, particularly n-PFOS, were found to disrupt endocrine function and harm health.
Researchers at Tokyo University of Science propose approximate domain unlearning (ADU) algorithm, which differentiates between domains while preserving generalization capability. This approach enables flexible AI configuration suited to individual practical scenarios.
University of Missouri researchers are combining in-home sensor technology with artificial intelligence to monitor daily changes in ALS patients' health. The system uses machine learning to estimate a patient's score on the ALS Functional Rating Scale Revised, predicting potential problems before they occur.
Researchers explore ways to understand and control multiple errors affecting machine tool accuracy, combining traditional models with data-driven approaches and digital twin technology. This enables more integrated systems that can monitor themselves, predict changes, and adjust behavior automatically.
A team of researchers has developed a detailed open map of emerging technologies, grouping 23,000 plus technologies into a multi-level map. The Cosmos 1.0 framework uses machine learning to analyze Wikipedia pages, books, and patents.
A cross-sectional study found that US population faces significant challenges with nervous system disorders, impacting 180.3 million people, mainly due to stroke, Alzheimer's disease, diabetic neuropathy, and migraine conditions.
Withdrawal of tirzepatide after 36-week treatment led to 25% or greater weight regain in most participants within a year, reversing initial cardiometabolic parameter improvements. Continued obesity treatment is crucial for sustained benefits.
Researchers identified a targeted drug that blocks a specific genetic pathway to reverse tumor-driving cellular interactions, potentially restoring DNA function and benefiting patients with synovial sarcoma. The study's findings endorse a promising strategy to improve outcomes for this rare but deadly cancer.
Approximately 1 in 30 clinical trials were disrupted due to grant funding terminations, disproportionately affecting infectious disease and prevention studies. The study emphasizes the need for sustainable financial support to ensure trial operations and participant safety.
Rapid rise in early measles vaccination observed in February 2025, ahead of CDC guidelines. The study suggests clinician and parental concern drove increased vaccination rates.
A study found that higher consumption of ultraprocessed foods is associated with an increased risk of developing early-onset colorectal cancer precursors. The research highlights the importance of improving dietary quality to mitigate the rising burden of early-onset colorectal cancer.
A recent study finds that artificial intelligence has a negligible effect on global greenhouse gas emissions. The researchers' analysis of US energy consumption and AI use across industries revealed that the energy usage from AI in the US equals the energy consumption for all of Iceland, but not noticeable on a global scale.
A recent FAU Engineering study leverages quantum computing to enhance the accuracy of chronic kidney disease (CKD) diagnosis. The research team developed and compared two automated systems: Classical Support Vector Machine (CSVM) and Quantum Support Vector Machine (QSVM). CSVM achieved remarkable 98.75% accuracy, while QSVM reached 87....
Researchers developed CellWhisperer, an AI method and software tool that links gene expression with descriptive text across millions of biological samples. It provides a virtual AI-based colleague to support biologists in their research, making biomedical data exploration easier and more exciting.
Researchers developed a novel topology-aware multiscale feature fusion network to enhance EEG-based motor imagery decoding. The TA-MFF network achieves excellent classification performance, outperforming state-of-the-art methods by leveraging spectral-topological data analysis-processing and inter-spectral recursive attention.
The FAU College of Engineering and Computer Science has established the 'Ubicquia Innovation Center for Intelligent Infrastructure' to develop transformative technologies. The center will empower students and faculty to create AI-First solutions for a smarter, more connected world.
Researchers from The University of Osaka developed MicroAdapt, a groundbreaking self-evolving edge AI technology that enables real-time learning and forecasting capabilities within compact devices. It achieves up to 100,000 times faster processing and 60% higher accuracy compared to state-of-the-art deep learning methods.
Pusan National University researchers develop a novel prompting technique to improve ChatGPT's accuracy in predicting fashion trends. The study reveals that ChatGPT can capture emerging themes and identify new trends not found in existing data.
A new study by the University of Ottawa exposes how video game studios are violating children's privacy rights. Researchers analyzed 139 privacy policies and found none fully comply with existing legal frameworks.
Optical computing harnesses light to accelerate feature extraction in AI applications. The new system, OFE2, achieves a 12.5 GHz operating rate and 250.5 ps latency, outperforming traditional digital processors.
A new study by Mass General Brigham researchers found that daily step counts of 4,000 or more are associated with a 26% lower mortality risk and 27% lower cardiovascular disease risk in older women. The study suggests that even sporadic high-intensity exercise can have significant health benefits.
The Global Pathogen Analysis Platform (GPAP) will enable low- and middle-income countries to conduct research and surveillance of infectious diseases independently. The platform aims to prevent disease outbreaks from developing into pandemics by detecting genetic sequences of potential pathogens.
A low-cost smartphone imaging system called mDOC combines autofluorescence and white light imaging with machine learning to accurately identify oral lesions requiring specialist referral. The system achieved an area under the ROC curve of 0.778, outperforming dental providers in sensitivity and specificity.
The Variant Workbench enables researchers to explore genetic data in a single, integrated workspace, linking genomic information with clinical conditions. By reducing data complexity, the tool facilitates scientific discovery and accelerates pace of research.
A new project aims to enhance workforce readiness in molecular bioscience by creating open-access resources and modules tailored to student needs. The Molecular Data Education Hub will host instructional materials and case studies for instructors to implement into their courses.
Researchers at the University of Missouri have developed an AI-powered method to detect hidden hardware trojans in chip designs, offering a 97% accurate solution. The approach leverages large language models to scan for suspicious code and provides explanations for detected threats.
A study published in JAMA found that both low and high increases in social media use during early adolescence are negatively associated with cognitive function. Specifically, adolescents with higher or lower social media use tend to perform poorly in certain aspects of cognition.
A new study found that COVID-19 work absences have become a year-round phenomenon in the US labor market, similar to pre-pandemic influenza season conditions. Nationally representative data can help monitor public health crises and inform policy decisions.
Researchers found that the addition of new hierarchical layers occurred neither at the start nor end of growth periods, but rather smoothly as firms expanded. Smaller firms tend to add layers soon after growth begins, while larger firms have lower levels of managerial resources at the end of growth periods.
The research team's Cord-Approx strategy coordinates drivers to assign different street parking spots using statistical predictions and an optimal matching algorithm. This approach significantly reduces parking search time, with drivers finding a spot in 6.7 minutes on average.
A prospective cohort study found that young adults experiencing unfavorable patterns of cardiovascular health are at a marked increased risk for incident cardiovascular disease. Achieving and maintaining high cardiovascular health throughout young adulthood is crucial for preventing later-life cardiovascular disease.
A large-scale study uncovered a strong connection between osteoporosis and rotator cuff tears, finding that individuals with osteoporosis are 1.56 times more likely to suffer an RCT. The study also identified common genetic variants influencing both conditions, suggesting a possible biological explanation for the link.
Researchers developed a novel spectroscopic approach to precisely analyze molecular interfaces at material surfaces. The technique uses gap-controlled infrared absorption spectroscopy, combining conventional ATR-IR with advanced data analysis, allowing for the isolation of interfacial molecular signals.
A new 'future-guided' AI method developed at the University of California, Santa Cruz, has shown significant improvements in predicting seizures using brain wave data. The technique operates with two deep learning models working together, improving predictions further into the future by transferring knowledge.