Data Science is a multidisciplinary field that involves extracting knowledge and insights from data using scientific methods, processes, algorithms, and tools. It combines aspects of statistics, mathematics, computer science, and domain expertise to analyze and interpret data, uncover patterns, make predictions, and solve complex problems. Data scientists utilize techniques such as data mining, machine learning, statistical modeling, and data visualization to extract valuable information and support data-driven decision-making in various industries and domains.
Texas A&M researchers have created a new AI-driven method called Symbolic Modeling that outperforms traditional asset pricing models by uncovering hidden market dynamics. The model improves prediction accuracy while offering a unified approach to handling diverse financial datasets.
Researchers at Mount Sinai have developed an AI model, PFTSleep, that analyzes entire nights of sleep with unprecedented accuracy. Trained on over 1 million hours of data, it classifies sleep stages more effectively than traditional methods, paving the way for advanced clinical applications.
AI has the potential to revolutionize health care by streamlining workflows, enhancing diagnostics, and improving patient outcomes, but barriers such as data privacy, high costs, and regulatory challenges slow its adoption. This comprehensive review offers a roadmap to overcome these hurdles and unlock AI's full potential in medicine.
Researchers from the Chinese Academy of Sciences emphasize the urgent need to align AI data systems with the complex, multi-level nature of scientific data to improve AI performance and reliability. They call for global standards and frameworks to structure data properly and foster AI's healthy development.
Researchers have developed ProtoSnap, an AI-driven approach that precisely identifies and reproduces cuneiform characters, making ancient script interpretation more accurate and accessible.
Researchers from KIIT and Chandragupt Institute of Management explore how machine learning transforms big data challenges into opportunities, enabling industries to harness vast data resources effectively.
Researchers have developed DeepGuard, an AI-powered tool that accurately detects fake images and traces their origins, enhancing security and preventing misinformation.
Researchers at Jefferson Lab developed an AI-based system, DIDACT, to optimize high-performance computing clusters by continually learning and selecting the best-performing model daily, reducing system downtime and costs.
Scientists at NYU have developed an AI model that learns how humans generate goals by studying how they create games, potentially advancing AI's understanding of human intentions.
LLM4SD is a cutting-edge AI tool that can analyze scientific literature, generate hypotheses, and predict molecular properties with high accuracy, making scientific discovery faster and more transparent. The open-source system also provides explainable insights, unlike traditional black-box validation tools.
The European Centre for Medium-Range Weather Forecasts (ECMWF) has launched the Artificial Intelligence Forecasting System (AIFS), a cutting-edge AI-driven model that improves weather prediction accuracy by up to 20% while reducing energy consumption by 1,000 times compared to traditional methods.
Researchers developed an AI system that improves tracking of urban green spaces using satellite imagery, significantly enhancing accuracy and revealing disparities in vegetation distribution.
Researchers at the University of Navarra have developed a novel AI framework that enhances fairness and reliability in machine learning models used for critical decision-making, reducing biases linked to race, gender, and socioeconomic status.
San Francisco State University researchers created a step-by-step machine-learning tutorial to predict antibiotic resistance, making complex concepts accessible to beginners in biology and health sciences.
Scientists at the University of California, Riverside, have developed an unsupervised machine learning tool that identifies patterns in LIGO's environmental data, reducing noise and improving gravitational wave detection.
Researchers have developed ProtET, a cutting-edge AI model that uses multi-modal learning to enable precise, text-guided protein editing, paving the way for breakthroughs in biotechnology and medicine.
DeepSeek has developed an agile AI model that outperforms larger systems despite using less advanced hardware, reshaping global AI competition and policy discussions.
Researchers at West Virginia University are developing an interdisciplinary curriculum to equip humanities faculty with the tools to explore AI's ethical, social, and technical dimensions and integrate AI into their courses.
Research introduces an explainable AI model that predicts ICU length of stay with 90% accuracy while providing evidence-based insights for informed decision-making. This innovative approach aims to optimize resource allocation, reduce overcrowding, and improve patient outcomes.
Research explores how Natural Language Processing (NLP) models like ChatGPT revolutionize understanding and generating human language. It delves into their mechanics, training processes, potential applications, and ethical considerations in AI's rapid evolution.
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