Articles tagged with Informatics
Researchers develop a new method to reconstruct the states of complex nonlinear systems based on time series data. The approach optimizes reconstruction parameters by focusing on the geometric structure of attractors, resulting in improved accuracy.
A study analyzed perspectives on personal health records from cancer patients and providers, highlighting the need for discussions about record uses. Implementing PHRs more widely, tailoring them to specific conditions, and making them user-friendly are next steps to improve patient-centered care.
Researchers used a contrast pattern mining algorithm on publicly available data from 16,000 participants in the T1D Exchange Clinic Registry. The study found individuals with an immediate family history of Type 1 diabetes were more frequently diagnosed with hypertension and other co-occurring conditions.
Rising temperatures are causing the world's coldest forests to shift northward, threatening biodiversity and increasing wildfire risks. Soil nutrient availability also plays a key role in the response of boreal vegetation to climate change.
Researchers propose using NFT digital contracts to enable patients to specify who can access their personal health information and track sharing. This could help democratize health data and give individuals more control over their health information.
Researchers discovered a small fraction of diatom cells participate in sexual reproduction, while others block growth and reduce nutrient absorption. This phenomenon occurs in nutrient-rich conditions, representing a paradox for microalgae that usually compete for resources.
The Epstein Family Foundation has donated $50 million to USC and UC San Diego to accelerate Alzheimer's research and discover effective therapies for the disease. The collaboration aims to compress study design, patient recruitment, and clinical trials to expedite the discovery of better treatments and a cure.
Researchers simulated an attack that falsified mammogram images, fooling both AI breast cancer diagnosis models and human radiologist experts. The study highlights the need to develop ways to make AI models more robust to adversarial attacks, which could lead to incorrect cancer diagnoses.
Researchers developed an AI technique to predict material properties using a small number of experiments, improving accuracy and facilitating digital transformation in materials development. The technique uses Bayesian optimization and incorporates measurement data into machine learning models.
A new study published in BMJ Health & Care Informatics examines decades of dashboards designed to communicate health data, highlighting the need for user-centered design and effectiveness testing. The research aims to guide the development of dashboard enhancements and customizations that support informed decision-making.
Researchers trained a GAN to generate novel refractory high-entropy alloys with specific properties, surpassing human intuition and guesswork in material design. The model produces alloy compositions in milliseconds, offering a promising tool for determining suitable materials.
The grant aims to educate diverse students for vital jobs in public health informatics and technology. UMass Lowell will offer new undergraduate and graduate programs, as well as certificates, to increase representation from underrepresented communities in the public health IT workforce.
The study analyzed data from 8,502 genetically high-risk children and found that half developed type 1 diabetes before age 6, while the other half developed it between ages 6 and 12. The findings suggest a different form of type 1 diabetes emerges in children as they grow older.
Researchers create maps of senescence in heart and lung cells, comparing different types of senescent cells across the lifespan. The goal is to understand how senescent cells contribute to age-related diseases and develop therapies called senolytics.
A new research center will use genomic data and socioeconomic factors to better predict health outcomes in individuals of diverse ancestry. The center aims to develop computational tools to combine large datasets and analyze them for consistent relationships among admixed populations.
Researchers Boevé and Giot translated insect defense chemicals into sounds, measuring human reactions. The study found that the responses by ants and humans are correlated, indicating that sonification can approximate real-world predator-prey interactions.
Researchers from UTHealth and Baylor College of Medicine recommend that EHR developers annually assess their products to ensure safety recommendations are met. The authors suggest three strategies to complement the new CMS rules, aiming to distribute responsibility for safety improvements evenly between designers, developers, and users.
Lehigh University researchers are developing a model to understand the impact of grain growth on material properties. The project aims to create new materials informatics methods, innovative stochastic differential equations, and models of grain growth to improve material performance and reliability.
Researchers developed a method to transform uncertainty-unaware controller models into robustified models that can safely behave under uncertainty. The method generates formulas representing the degree of uncertainty a controller can tolerate, enabling flexible analysis and consideration of real-world deployment situations.
The Regenstrief Institute emphasizes the importance of algorithmic performance in healthcare, highlighting the need for systematic surveillance and vigilance to address inherent biases. Studies have shown that debiasing methods can help address disparities represented in data used to develop AI approaches.
A team from Regenstrief Institute created an emergency EMR for Indianapolis first responders in just one week using OpenMRS, a global open-source electronic medical record system. The system allowed for quick registration of patients, collection of basic clinical information, and transmission to the Indiana health information exchange.
Researchers used materials informatics to develop new TADF materials, increasing efficiency by 20-40% and lifetimes up to 10 times longer. Co-Host technology improved electric charge balance, expanding recombination sites and enhancing colors for full-color displays.
A University of Central Florida researcher studied three aging-in-community programs in Florida to examine the impact of supportive communities on older adults. She found that higher education levels were linked to lower perceptions of independent living, while neighborhood social cohesiveness was more common among married individuals....
Researchers have developed a new software method for compressing quantum circuits, reducing the size and runtime of large-scale fault-tolerant quantum computers. This compression technique achieves up to 77% reduction in volume, potentially enabling the realization of real-world quantum computers years ahead of schedule.
The National COVID Cohort Collaborative (N3C) is a centralized analytics platform storing vast amounts of medical record data from people tested for COVID-19. Regenstrief serves as the national project's Honest Data Broker, creating more complete and informative data sets while ensuring patient privacy.
A researcher at Northern Arizona University is developing AI-powered drones that can monitor themselves and each other in different scenarios. The project aims to enable autonomous drones to respond to environmental and behavioral factors, improving their performance in various applications such as traffic control and surveillance.
A team of researchers has proposed a method to use time crystals to simulate massive networks with very little computing power. They used graph theory and statistical mechanics to fill the gap in understanding time crystals and their applications.
The Vaccination Game, developed by University of Oxford researchers, challenges players to deploy limited doses of a virtual vaccine to control the spread of a disease modelled on influenza. By replaying the game, players can improve their strategy and save more lives.
A study of over 4,000 tweets reveals that only a small percentage of Twitter users use JUUL to stop smoking or improve their health. Most tweets about JUUL are positive and discuss first-person usage or the brand's products.
Researchers from Kazan Federal University developed a quantum algorithm to solve the Dyck problem, which is crucial for parsers and compilers. The new algorithm can solve the problem in just 40 seconds on a quantum computer.
Eduardo Lopez Atencio and his collaborators are analyzing agent search methods in a constrained network environment to help the US Army workforce stay focused on strategic goals. This analysis will be applied to forecast workforce behaviors across an extended planning horizon.
Researchers have developed a method to reduce noise and resources required for quantum information transmission, paving the way for a quantum internet. Quantum multiplexing allows for the combination of multiple pieces of information into one photon, reducing the need for separate stamps and enabling significant resource reduction.
A recent study found that hospitalized NYC COVID-19 patients had higher rates of kidney complications and needed mechanical ventilation more frequently than other patient groups. The study analyzed data from over 1,000 patients treated at NewYork-Presbyterian/Columbia University Irving Medical Center between March and April 2020.
A recent study analyzed 50 COVID-19-related apps and found that most require access to users' personal data, but only a few indicate secure storage. The researchers warn that governments' use of tracking technology could lead to mass surveillance and chilling effects on individual privacy.
A large study evaluated de-identified data from electronic dental records of 217,887 patients from 99 solo or small dental practices across the US. The study found that it's feasible to mine EDR data to learn which dental therapies work and which don't, empowering quality improvement by individual dentists.
Charisse Madlock-Brown's R15 grant aims to identify costly multimorbidity groupings and disease progression. Her project will use a large patient dataset to develop intervention strategies, contributing to simpler, less expensive treatment options.
Two University of Cincinnati students developed an interactive dashboard to track COVID-19 cases and deaths. The COVID-19 Watcher displays data from every county and metropolitan area, allowing users to compare their city's progression with others.
A new poll suggests that while older adults use online physician ratings, they are cautious in their approach, prioritizing factors such as wait time and doctor experience over the number of stars. Meanwhile, only a small percentage of those polled have actually posted reviews or ratings of doctors online.
A team of researchers at Medical University of South Carolina enhances an existing informatics tool to better identify Emergency Department cases of nonfatal opioid overdose. The enhanced tool uses natural language processing to analyze clinical notes and provide real-time information on opioid addiction, enabling more intelligent clin...
A prototype of a cloud-based informatics and resource-discovery tool will be built to help CTSA hubs measure their impact and compare efforts. The e-SPARC tool aims to provide a one-stop shop for investigators planning trials, while also supporting NCATS monitoring and improvements.
A study published in Nature Neuroscience found that larger green areas in urban neighborhoods are associated with higher wellbeing. Participants who spent more time in green spaces showed reduced activity in the brain region responsible for processing negative emotions.
The multi-society statement focuses on three areas: data, algorithms, and practice. It emphasizes the importance of ethical use of AI in radiology, ensuring benefits and harms are distributed fairly among stakeholders. Radiologists will need to acquire new skills to work effectively with AI tools.
A research group used materials informatics to identify a high-capacity and stable organic material for lithium-ion secondary cells. By combining empirical knowledge and machine learning, they successfully obtained a material with improved capacity, durability, and quick charge-discharge property.
Researchers found that men and women exhibited higher pain thresholds and lower sensory pain ratings when their partners were present. The study suggests that partner empathy can buffer affective distress during pain exposure, even without verbal or physical contact.
Researchers created decision models to predict which patients need more treatment for depression than their primary care provider can offer. The algorithms provide actionable information to clinicians, helping them identify high-risk patients and refer them to mental health specialists.
Regenstrief Institute researchers are presenting their work on artificial intelligence, public health informatics, disease surveillance, and electronic care planning for chronic diseases. They will also discuss opportunities for advancing the use of electronic health record data.
A machine-learning model was developed to predict surgical-case duration, with accuracy improved from 30% to 40-50% in some cases. The study used data from over 45,000 surgeries performed by 92 surgeons, finding that the greatest variability in estimates came from individual surgeon approaches.
A new study by the German Sport University Cologne compares the tactical performance of male and female football players in Europe, using advanced analysis methods. The findings aim to contribute to the development and professionalization of women's football, while promoting public awareness of the sport.
Researchers from Lehigh University used materials informatics to predict a class of high-entropy alloys with superior mechanical properties. The new method, combined with experimental tools like electron microscopy, revealed alloys with hardness values exceeding initial expectations by a factor of 2.
Researchers found that standardizing addresses had the greatest impact on data matching, increasing accuracy by nearly half. This improvement can lead to better patient safety, improved care quality, and reduced costs.
The project aims to create a personalized portal where people with epilepsy can manage their disease and find relevant information. It will integrate data from social media, electronic health records, and scientific literature to provide targeted recommendations and visualizations.
A recent UTHealth-led survey revealed that only 19.3% of healthcare organizations in the US and Australia have fully implemented voluntary guidelines for safe e-health record management. The study found significant variation in adherence rates across different domains, suggesting factors such as budget constraints, personnel skill mix,...
Researchers designed a computer simulation that added correlated noise to the path of energy transfer, significantly accelerating it. This finding challenges traditional views of noise as a hindrance in energy transport, opening up new possibilities for optimizing energy efficiency.
The consulting firm is founded by four computer science experts from Saarland University to provide sound advice on data analysis. Data Science Consulting focuses on collecting, cleaning and merging data, as well as removing errors, maintaining data, setting up a scalable architecture and defining critical characteristics for analysis.
A team of researchers is developing tools to help museums measure visitor engagement and modify exhibits to enhance engagement. The project will use multiple technologies, including motion-tracking and facial-monitoring, to collect data on visitors' interactions with educational exhibits.
Researchers have made counter-intuitive observations in hybrid quantum systems, where cooling processes can lead to heating. The study revealed that symmetries in the system can cause decay to excite components of another subdomain, resulting in a heat-up effect.
A study of a billion Twitter posts found that users with darker skin tones modified emojis more often to express their identity, while users with light skin were less likely to make changes. The results also showed that darker skin tones were underrepresented globally, but still widely used.
A new evaluation method for AI predictability has been developed by Kyoto University researchers, tackling issues of accuracy and bias in traditional metrics.
The University of Pittsburgh Graduate School of Public Health shares a training protocol for community health center leaders and staff on using big data for informed decision-making. The protocol provides access to over 100 training programs, webinars, and tools to address specific needs in health informatics.
Using electronic health records, UCSF researchers mapped over 435,000 patient location changes and identified a critical CT scanner in the Emergency Department as a significant source of exposure-related C. diff infections. This analysis led to improved cleaning practices and bolstered infection prevention strategies.