The generation of synthetic data in healthcare has emerged as a promising solution to surmount longstanding challenges inherent in the use of real patient data.

In the process of data collection of wind power generation, due to equipment, human and other reasons, data is often missing. Therefore, it is necessary to fill in missing data to ensure the accuracy ...

In this piece, we demonstrate how to conduct age-period-cohort analysis, a statistical tool, to determine the effects of generation.

PURPOSESynthetic data are artificial data generated without including any real patient information by an algorithm trained to learn the characteristics of a real source data set and became widely used ...

Abstract To address the difficulty of training high-quality models in some specific domains due to the lack of fine-grained annotation resources, we propose in this paper a knowledge-integrated ...

Synthetic data— artificial data that closely mimic the properties and relationships of real data—is not a new idea but recent technological advances have brought it to prominence as a potentially ...

Power system dispatching and operation rely on massive operation data, especially for data-driven methods. However, power systems often face challenges with insufficient or imbalanced data, ...

Quantitative Research Methods Enhance your social science degree with quantitative training in applied data analysis to increase your career prospects across multiple professions.

To test the LAB method, IBM Research generated a synthetic dataset with 1.2 million instructions and used that data to train two open-source LLMs. The results show that both LLMs performed on par or ...

These diverse research efforts underscore a global trend towards integrating synthetic data generation within both clinical research and operational healthcare environments.