Course by tag

Data Science in Clinical Practice

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).

Data Science in Clinical Practice

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).

Data Stewardship

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).

Data Stewardship

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).

Cognitive Neuropsychology: From Patients to Functional Models

As an advanced training in Cognitive Neuropsychology, the course aims to teach PhD students how to collect and interpret patient data in order to test cognitive theories and build cognitive models. The emphasis will be on 'doing research'. Candidates will get an acquaintance with standard neuropsychological testing, will be shown examples of patients cases, case statistics and will build, run and analyse their own experiment. A special training in reviewing and reporting is included.