Articles tagged with Digital Data
Researchers found that users pay a price for free mobile apps, including reduced focus, sleep deprivation, and loss of physical contact. Users prefer to make one-time purchases to protect their privacy over using services with hidden costs.
The CityUHK team develops a new federated learning technology integrated with research knowledge graphs and large language models to digitally transform STI services. This will create a comprehensive, domain-specific knowledge base and provide intelligent assistant services for researchers.
Karen Jo Matsler, a UTA professor, is being honored for her extensive contributions to physics education and her efforts to support educators nationwide. Her Quantum for All initiative aims to integrate quantum concepts into high school science instruction, preparing students for careers in quantum technology.
Researchers develop novel workflows to digitize and future-proof biodiversity data using digital specimen DOIs and nanopublications. This enables scientists to link digital specimens to various databases, facilitating inter-institutional scientific work and saving time for AI systems.
A study using a smartphone-based wayfinding task identified individuals with increased risk for dementia, based on their movement patterns and spatial memory. The research provides promising insights into the potential of digital technologies for early detection and monitoring of Alzheimer's disease.
Research by Alesha Serada at the University of Vaasa highlights that NFTs in games derive value from social relations and community, rather than rarity or price. The study, focusing on CryptoKitties, suggests a three-dimensional model for value creation, including subjective player value and collective community-created value.
Researchers at MIT developed a security protocol that leverages quantum mechanics to guarantee secure data transmission during deep-learning computations. The protocol encodes data into laser light, making it impossible for attackers to copy or intercept information without detection.
SEARCH aims to accelerate healthcare innovation by generating FAIRified synthetic data for use in AI/ML models, enabling large-scale data collaborations while preserving privacy and compliance. The hub will deliver reliable methodologies for synthetic data generation, significantly increasing the availability of interoperable datasets.
A new study published in PLOS Mental Health found a relationship between daily sunlight exposure, physical activity, and depressed state. The research used wrist-based activity sensors to collect data from individuals with depression and those without, revealing that more depressed states were associated with lower daytime activity.
Researchers have developed an AI technology that can analyze mammary tissue biopsies to identify signs of damaged cells, a key indicator of breast cancer risk. The study found the AI was far better at predicting risk than current clinical benchmarks, offering improved treatment options for women.
A study analyzing health data from 780 infants found that early signs of asthma can be predicted by observing dynamic symptom development during the first year. Genetic predisposition, air pollution, and infections were key risk factors contributing to the child's respiratory system adaptation.
This study suggests that gamified digital mental health interventions can be an effective treatment option for youth with ADHD or depressive disorders. The findings provide new information for pediatricians and healthcare professionals seeking innovative solutions for pediatric mental health care.
The integration of artificial intelligence in intratumoral immunotherapy can refine diagnoses, guide interventions, predict treatment responses, and adapt therapeutic strategies. This enables the enhancement of patient outcomes, including improved survival rates and quality of life.
A new study has identified key factors to build food resilience in Sub-Saharan Africa, including diversifying suppliers, empowering local farmers, and promoting sustainable practices. The proposed blueprint aims to enhance self-sufficiency and reduce reliance on external sources.
The UC3M-Universia Chair aims to address the challenges of large tech companies' data use and create a new, transparent and fair personal data economy. Researchers will develop models and algorithms linked to AI that are interpretable and unbiased.
Researchers from the University of California, Davis, present a comprehensive framework for analyzing longitudinal activity and behavior. By employing advanced statistical techniques, they explore the relationship between activity and age-at-death in Mediterranean fruit flies, shedding light on potential links to human lifespan.
Researchers analyzed 2 million Google Street View images to explore the utility of digital data in informing public health decision-making. They found that neighborhoods with more crosswalks had lower rates of obesity and diabetes, but no significant link was found between sidewalks and health outcomes.
A 10-year study found that digital breast tomosynthesis increases cancer detection rates and reduces advanced cancers compared to conventional 2D digital mammography. DBT detected more aggressive cancers at an earlier stage than digital mammography, leading to improved cancer detection and lower recall rates.
A Cornell University-led research team found that using a technique called 'cultural prompting' reduces bias in large language models like ChatGPT for over 100 countries. The approach involves specifying a cultural identity directly in prompts, adapting to different cultural norms and values.
A systematic review of pharmacogenomics clinical decision support systems found that e-health tools can help integrate personalized medicine into everyday clinical practice. However, current implementation is limited, particularly in non-US healthcare systems.
Rice University researchers developed ElasticDiffusion, a method that separates local and global signals to create non-square aspect ratio images without visual imperfections. The new approach can improve consistency and realism in AI-generated images, but still requires significant computational power.
Hassan's research focuses on creating advanced techniques for collecting and integrating data provenance to enhance threat detection. The project also includes educational initiatives to prepare the next generation of cybersecurity professionals.
The new Corporate Lab aims to advance collaboration between industry and public sector researchers to address real-world challenges in sustainable living and digital technologies. It will develop and trial novel digital technologies prioritizing sustainable ecosystems and lifestyles, including energy-efficient AI algorithms, green clou...
A new smartphone-based digital holographic microscope enables precise 3D measurements and has potential applications in medical diagnostics, education, and resource-limited settings. The portable device uses a simple optical system created with a 3D printer and calculates reconstructions based on a smartphone.
A novel deep learning model, DS-ViT-ESA, was developed to predict lithium battery lifespan with high accuracy using only a small amount of charging cycle data. The model achieved low prediction errors even when tested on unseen charging strategies, demonstrating its zero-shot generalization capability.
Underwater noise pollution from human activities significantly impacts the ability of orcas to hunt successfully in the Salish Sea. The study found that increased ambient noise levels, particularly around vessel propellers, interfere with echolocation behavior and hunting efforts. This hindrance affects females more than males, potenti...
Researchers at Thomas Jefferson University have developed a novel screening tool to measure digital health readiness, addressing barriers to telehealth adoption. The tool assesses technical readiness and quality of care concerns, with promising results in improving equity.
Researchers at Klick Labs developed an AI technique using vocal biomarkers to predict chronic high blood pressure with up to 84% accuracy. The study used machine learning to analyze hundreds of indiscernible vocal biomarkers, including pitch variability and speech energy distribution patterns.
Generative AI is revolutionizing oncological imaging by expanding datasets and improving image quality. This technology enables predictive oncology and personalized cancer screening, offering new hope in the fight against cancer.
Researchers at Tel Aviv University used modern technologies to challenge the long-held myth that the Roman siege of Masada lasted three years. The study found that the siege actually lasted no more than a few weeks, using precise measurements and 3D digital modeling to calculate the time it took to build the siege system.
A team at NUS Yong Loo Lin School of Medicine leveraged an artificial intelligence-derived platform, CURATE.AI, to guide treatment for a patient with Waldenström macroglobulinemia, a rare blood disorder. The trial demonstrated substantial improvement in red blood cell levels and minimised side effects.
Researchers analyzed 650 million tweets to identify new words and tracked their adoption. Words used by central users persisted longer, while those with less central positions had a rapid rise and decline. The study reveals the predictive power of social network position in shaping language.
Researchers found that digital consultations significantly improved medication adherence among heart failure patients, with 28% receiving optimal medication combinations after 12 weeks. The study also showed no negative impact on patient satisfaction or quality of life.
A new editorial in Oncoscience explores the application of functional information to adapt radiation therapy to individual patients. This approach aims to reduce uncertainty and improve outcomes in cancer treatment by analyzing signal data uncertainty.
Researchers explore emerging role of Graph Filtration Learning (GFL) in revolutionizing HCC imaging analysis. GFL captures complex topological features inaccessible to traditional pixel-based methods.
A new course launched with funding from the UK Space Agency to address the growing skills gap in software, data, and AI for the UK space sector. The Securing the future of space: Space Software and Data/AI CPD programme will equip mid-career professionals with expertise in AI and data-science.
A new study by Binghamton University researchers found that virtual team members who receive inspiring responses from others are more likely to be viewed as emergent leaders. To become an effective leader in a virtual setting, it's essential to pay attention to how the audience responds to your message and support others' ideas.
A new AI-based digital platform has been developed to analyze tissue sections from lung cancer patients, making diagnosis faster and more accurate. The platform uses algorithms that enable fully automated analysis of digitized tissue samples, allowing for personalized therapy based on molecularly specific genetic changes.
A study of 1,300 emerging adolescents found that higher parental technoference levels were associated with increased anxiety symptoms, inattention, and hyperactivity. The findings highlight the need for parents and emerging adolescents to discuss digital technology use and mental health as part of routine care.
Researchers found that 49% of respondents experienced a moderate to extreme impact on their mental or emotional wellbeing after encountering negative experiences in virtual environments. The study highlights the need for metaverse companies to instill clear regulatory frameworks for safe virtual spaces.
Researchers at UMass Amherst discovered a vulnerability in digital wallet security that can be exploited by malicious actors even if the rightful cardholder doesn't use a digital wallet. The study found that banks prioritize convenience over security, leaving users' credit cards susceptible to unauthorized transactions.
A new study found that digital health tools can improve health and wellbeing by keeping people active, boosting steps, and improving diet and sleep. The research synthesised data from 206,873 people across 47 studies, indicating that electronic and mobile health interventions can help people achieve positive outcomes.
Researchers have developed a chip-based quantum system that can detect unauthorized access in quantum communication, using entangled four-photon states. This technology has the potential to strengthen data security and protect sensitive information from cyber threats.
EPFL researchers have created an energy-efficient method for nonlinear computations using scattered light from low-power lasers. The new approach is scalable and up to 1,000 times more power-efficient than state-of-the-art digital networks, making it suitable for realizing optical neural networks.
A new study by Lancaster University highlights that women are more likely than men to experience 'digital overload' and burnout due to their greater use of digital technologies in both work and family lives. The research emphasizes the need for gender-egalitarian work-from-home arrangements and policies to address this issue.
Researchers developed a machine learning-based system to analyze satellite data and provide farmers with information on pasture productivity and quality. The approach uses remote sensing and AI-driven processing to gather data on large areas, providing a scale-neutral solution for small- and large-scale farms.
Researchers from Stellenbosch University discovered that using work-related content during golf sessions reduces performance, whereas personal activities have little to no effect. The study suggests a clear distinction between leisure and professional use of smartphones in recreational settings.
A new study found that meeting partners online is positively linked to relationship success among those who have social media presence on their relationships. However, the link was absent among individuals without this social media presence, particularly in marital relationships.
Researchers at TUM have mapped the interactions of 144 active substances with around 8,000 proteins using a new method called decryptE. This study could help identify previously unknown potential benefits of existing drugs and improve treatment outcomes for patients.
Researchers at Pohang University of Science & Technology have developed a novel analog hardware using ECRAM devices that maximizes AI computational performance. Their technique, which uses a three-terminal structure with separate paths for reading and writing data, demonstrates excellent electrical and switching characteristics.
Researchers found correlations between MIF and DDT levels with patient survival outcomes in melanoma patients. Higher CD74:MIF and CD74:DDT levels were associated with improved survival and enrichment of inflammatory markers.
A new study published in PLOS Digital Health found that machine learning models can reliably predict the disability progression of multiple sclerosis. The models were trained on data from 15,240 adults with at least three years of MS history and had an average accuracy of 0.71 ± 0.01.
A new study published in Nature Medicine found that people rate medical advice as less reliable and empathetic when an AI is believed to be involved. Despite this, respondents were still less willing to follow AI-supported recommendations compared to advice from human doctors.
Researchers found a significant association between the KIT M541L variant and mastocytosis diagnosis in patients with systemic and cutaneous mastocytosis. The variant was identified in 19 individuals, mostly diagnosed with systemic mastocytosis, but without significant differences in symptomatology.
A new method called D-REC uses a digital twin to predict which data users will need, improving edge caching decisions. The digital twin takes real-time data from the wireless network and conducts simulations to make accurate predictions.
A new study published in Aging explores the potential of three large DNA methylation datasets to identify biological age signals in dogs. The researchers found that biological age methylation clocks are affected by population stratification and require heavy parameterization to achieve effective predictions.
The study compares simpler-to-implement nonlinear encoding strategies with the performance of data repetition-based methods, revealing that data repetition enhances inference accuracy but compromises universal linear transformation capability. Phase encoding without data repetition offers a simpler alternative with comparable inference...
A USF study reveals that digital food ordering platforms significantly influence consumer behavior, often leading to more indulgent food choices and increased spending. The study found that 61% of digital orders were unhealthy, and consumers who are more proficient with technology may be less susceptible to the Google Effect.
A study found that large language models, despite accuracy in medical exams, fail to consistently request necessary examinations and often deviate from treatment guidelines. In comparison to human doctors, AI diagnoses achieved lower accuracy rates, highlighting concerns about their suitability for everyday clinical practice.
A new study published in JAMA Network Open found that mental health apps can significantly reduce symptoms of depression, anxiety, and suicidality in individuals waiting for their initial psychiatric appointment. The study, which involved over 2,000 patients, showed improvement in all groups, regardless of the app used.