Visualization of Diseases at Risk in the COVID-19 Literature
원문 초록
This paper presents a project, named VIDAR-19, able to extract automatically diseases from the CORD-19 dataset, and also diseases which might be considered as risk factors. The project relies on the ICD-11 classification of diseases maintained by the WHO. This nomenclature is used as a data source of the extraction mechanism, and also as the repository for the results. Developed for the COVID-19, the project has the ability to extract diseases at risk and to calculate relevant indicators. The outcome of the project is presented in a dashboard which enables the user to explore graphically diseases at risk which are put back in the classification hierarchy. Beyond the COVID-19, VIDAR has much broader applications and might be directly used for any corpus dealing with other pathologies.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Using Instruction-Tuned Large Language Models to Identify Indicators of Vulnerability in Police Incident Narratives
Harmonic-NAS: Hardware-Aware Multimodal Neural Architecture Search on Resource-constrained Devices
STRAPPER: Preference-based Reinforcement Learning via Self-training Augmentation and Peer Regularization
Unlocking the Use of Raw Multispectral Earth Observation Imagery for Onboard Artificial Intelligence
VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution
Continuous Indeterminate Probability Neural Network
토론
이 논문과 연결된 포럼 글이 아직 없습니다.