AI-aided evidence-based medical guidelines (TRAM)

Clip-art image of a doctor with checklist on PC

Medical guidelines are crucial tools for supporting clinical decision-making, improving care quality, and reducing variation in medical practice. These guidelines depend on systematic reviews of the scientific literature, but the sheer volume of publications makes the development and maintenance of high-quality, up-to-date guidelines increasingly time-consuming and resource-intensive.

The TRAM 辫谤辞箩别肠迟鈥Tooling for Rapid Assessment of Medical evidence鈥攅xplores how artificial intelligence (AI), particularly active learning, can support and accelerate this process. By integrating AI into the literature screening phase, TRAM aims to reduce workload while preserving methodological rigor, helping guideline development organizations keep pace with the latest evidence.

Progress

TRAM is a collaboration between Utrecht 木瓜福利影视鈥檚 AI & Knowledge Discovery Lab, the Knowledge Institute of the Dutch Federation of Medical Specialists, Cochrane Netherlands, and the Julius Center. The project has focused on developing and evaluating a pipeline in which AI supports the screening of scientific literature for use in medical guidelines.

In practice, the TRAM pipeline integrates tools like ASReview to prioritize relevant studies. A proof-of-concept study showed that this approach can substantially reduce the number of abstracts that need to be screened manually while still identifying nearly all relevant studies. This work is currently being extended to explore how AI might support other phases of the guideline development process, such as the weighing and interpretation of evidence.

Funding

This project and its resulting output are being funded by ZonMw, the Stichting Kwaliteitsgelden Medisch Specialisten (SKMS) and the Dutch Research Council in the 鈥淐orona: Fast-track data鈥 11 (2020/SGW/00909334)

People involved

  • Laura Hofstee PhD candidate and Project Lead
    The Knowledge Institute of the Dutch Federation of Medical Specialists, Utrecht 木瓜福利影视 
  •  Advisor
    The Knowledge Institute of the Dutch Federation of Medical Specialists 
  •  Advisor
    The Knowledge Institute of the Dutch Federation of Medical Specialists 
  •  Advisor
    Cochrane Netherlands and the Julius Center 
  • Rens van de Schoot Advisor
    Utrecht 木瓜福利影视

More info