Course by tag

Careful data curation and analyses are essential in developing machine learning algorithms, that may usefully contribute to solving problems encountered in routine healthcare. Nevertheless, many valuable contributions never transition from the computer to the bedside. Often implementation is never attempted, or they fail to get the relevant CE marking (or equivalent local standard), or their implementation fails to elicit the intended health benefit (failure due to lack of clinical utility).

Careful data curation and analyses are essential in developing machine learning algorithms, that may usefully contribute to solving problems encountered in routine healthcare. Nevertheless, many valuable contributions never transition from the computer to the bedside. Often implementation is never attempted, or they fail to get the relevant CE marking (or equivalent local standard), or their implementation fails to elicit the intended health benefit (failure due to lack of clinical utility).

Did you ever wonder how you can improve your data management and handling? Have you ever hoped for a clean and indisputable database that you could easily share with your collaborators? Understand the art of Data Stewardship and get a handle on your data! Data could yield great value when processed intelligently for medical data science but holds great risks when processing is lost in complexity. This online Data Stewardship course will guide you to steward your clinical data to aid data science developments, facilitate collaborative research, comply with privacy regulations, and ensure data integrity and quality. Together we will put data stewardship in practice with clinical decision-making tools, predictive models, and Artificial Intelligence (AI).

Did you ever wonder how you can improve your data management and handling? Have you ever hoped for a clean and indisputable database that you could easily share with your collaborators? Understand the art of Data Stewardship and get a handle on your data! Data could yield great value when processed intelligently for medical data science but holds great risks when processing is lost in complexity. This online Data Stewardship course will guide you to steward your clinical data to aid data science developments, facilitate collaborative research, comply with privacy regulations, and ensure data integrity and quality. Together we will put data stewardship in practice with clinical decision-making tools, predictive models, and Artificial Intelligence (AI).

This is a five-day course on structural equation modeling (SEM) using Mplus. In this course, SEM experts will teach you about the fundamentals of SEM and various types of longitudinal data analysis techniques, such as growth curves analysis, cross-lagged panel models, and dynamic structural equation modeling (DSEM). The course consists of in-depth lectures and computer lab meeting on the fundamentals of Mplus and on advanced longitudinal models.