Articles tagged with Data Analysis
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 guide has been launched to help tackle the growing threat of technology-facilitated domestic abuse against older people. The resource highlights practical ways to prevent and respond to digital forms of abuse, including how to secure access to bank accounts and lock smart devices.
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.
A study by University of Arizona researchers found that selecting the right data for flood insurance can significantly improve accuracy, speed, and predictability. The type of data used affects not only payout timing but also confidence in anticipating future payouts, influencing program costs.
Researchers have discovered myeloid cells in children's liver tumors that could be activated for treatment. This discovery provides new avenues for immunotherapy in childhood liver cancer.
Dr. Andreea Creanga, a leading maternal health expert, joins the University of Maryland School of Medicine as Chair of the Department of Epidemiology and Public Health. She will oversee initiatives in bioinformatics, data science, and maternal health.
A new study suggests that low-dose aspirin can prevent cancer in older adults based on individual characteristics. The analysis found varying treatment effects among participants, highlighting the need for personalized approaches to cancer prevention.
A new study challenges conventional assumptions about urban healthcare advantages by revealing that larger cities have proportionally fewer specialists per resident than smaller ones. Smaller cities often serve more patients per specialist, with some specialties like addiction medicine showing significant disparities in availability.
A systematic review and meta-analysis of 18 trials found GLP-1 RAs significantly improved glycemic and weight outcomes in children and adolescents with type 2 diabetes or obesity. However, gastrointestinal adverse effects warrant attention in long-term management.
A retrospective cohort study found that children of racial and ethnic minority groups receiving CPR had higher odds of in-hospital mortality. Additionally, the odds of in-hospital mortality among children receiving CPR were higher at hospitals with the highest proportion of Black patients.
Researchers are decoding animal decision-making using glass knifefish, exploring the trade-off between gathering information and acting on it. The study, funded by the NIH, aims to understand how animals make decisions in uncertain environments and may lead to breakthroughs in robotics and medicine.
Researchers developed a method to identify causal relationships between neurons solely based on spike train data, providing a new tool for understanding brain connectivity. The approach accurately detected bidirectional and unidirectional coupling between neurons, even in the presence of internal noise.
The new STROBE-Equity extension provides a framework for researchers to report health equity data and considerations in observational studies. This improved reporting can help knowledge users better identify and apply evidence relevant to populations experiencing inequities.
ConcreteSC technology achieves significant speed boosts and improved efficiency in next-generation wireless networks. The innovation integrates user tasks into communication processes, reducing computational complexity and increasing semantic meaning.
A new study introduces an optical imaging technique that uses autofluorescence to detect colorectal cancer in real time, offering a promising tool for improving cancer detection during endoscopic procedures. The technique achieved high accuracy rates and the potential to guide doctors during colonoscopy or surgery.
The study reveals data visualization primarily facilitates decision-making at the organizational and community levels, particularly for semi-structured problems. Recent trends indicate increasing support for broader types of decision-making, including individual-level and unstructured problems.
A cohort study found a higher prevalence of eating disorders among adolescents from lower socioeconomic backgrounds. The study suggests that reducing population-level socioeconomic inequalities may aid in preventing eating disorders.
MIST uses a hierarchical, rules-based classification system grounded in verified mineral formulas from the RRUFF mineral database. It accurately identifies hundreds of different mineral species from their chemical composition, even accounting for natural imperfections and vacancies found in real minerals.
Researchers developed a machine learning model that accounts for biological variability to identify optimal formulations for serum-free culture media. The model achieved approximately 1.6-fold higher cell density compared to commercially available products.
Astronomers have developed a protocol to detect supernovae within 24 hours of their explosion, using high-cadence sky surveys. The method involves rapid searches for candidates based on light signal absence and galaxy location, followed by spectroscopic observations to determine the type of supernova.
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.
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.
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 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 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.
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.
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.
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.
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.