DOME Registry: implementing community-wide recommendations for reporting supervised machine learning in biology.

ABSTRACT: Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The Data Optimization Model Evaluation (DOME) recommendations aim to enhance the validation and reproducibility of ML research by establishing standards for key aspects such as data handling and processing, optimization, evaluation, and model interpretability. The recommendations help to ensure that key details are reported transparently by providing a structured set of questions. Here, we introduce the DOME registry (URL: registry.dome-ml.org), a database that allows scientists to manage and access comprehensive DOME-related information on published ML studies. The registry uses external resources like ORCID, APICURON, and the Data Stewardship Wizard to streamline the annotation process and ensur

SUBMITTER: Attafi OA 

PROVIDER: S-EPMC11633452 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature