Computer Vision News Computer Vision News 42 "Datasets through the LookingGlass" is a webinar series focused on reflecting on the data-related facets of Machine Learning (ML) methods. We are building a community of enthusiastic researchers who care about understanding the impact that data and ML methods could have on our society. The webinar is part of “Making MetaDataCount” project and is organized by Veronika Cheplygina (left in the picture) and Amelia Jiménez-Sánchez (on the right) at IT University of Copenhagen. The team was recently joined by Théo Sourget, also affiliated at the IT University of Copenhagen, and Steff Groefsema from the University of Groningen. Steff kindly sent us this report. Datasets through the L king-Glass In the latest edition, several researchers presented their work on bias and dataset quality. Amelia Jiménez-Sánchez is a postdoctoral researcher at the IT University of Copenhagen. Her research focuses on learning feature representations from deep learning methods for medical image analysis and, in particular, addressing challenges like limited data, class-imbalance, noisy annotations, and data privacy in collaborative hospital settings. Amelia presented the work In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review. The presented research is the result of a year-long collaboration between around 50 different participants from academia, clinician practice and industry. During multiple webinar series and one in-person workshop, the participants discussed many challenges related to the quality of medical datasets. In her talk, Amelia presented a framework for a living review of medical imaging datasets, and also highlighted some well-known challenges related to the data quality of medical datasets. Her entire talk is in the following page. Want to know more about medical datasets and their research artifacts? Try the interactive demo!
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