Two of our papers were accepted for presentation at MI2024, 34th Medical Informatics Europe Conference, which will take place from August 25-29 in Athens, Greece.
“An Overview of Public Retinal Optical Coherence Tomography Datasets: Access, Annotations, and Beyond”, Anastasiia Rozhyna et al.
In ophthalmology, Optical Coherence Tomography (OCT) is a daily diagnostic and therapeutic tool for various diseases. Publicly available datasets are crucial for research but suffer from inconsistent accessibility, data formats, annotations, and metadata. This article analyzes different OCT datasets, focusing on properties, disease representation, and accessibility, aiming to catalog all public OCT datasets. The goal is to improve data accessibility, transparency, and provide new perspectives on OCT imaging resources.
“PICO to PICOS: Weak Supervision to Extend Datasets with New Labels”, Anjani Dhrangadhariya et al.
Using a weakly supervised approach, this work achieved an impressive F1 score of 85.02% in extracting clinical entities without labelled data. Leveraging data programming and resources like UMLS and NCBOBioportal, the workflow successfully extracts “Study type and design” from clinical trial abstracts in the EBM PICO dataset.
