15 citations · 24 across the 4 of their papers we have counts for
4 papers
MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images
Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout
Multi-modal fusion approaches aim to integrate information from different data sources. Unlike natural datasets, such as in audio-visual applications, where samples consist of "pai…
Towards dynamic multi-modal phenotyping using chest radiographs and physiological data
Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout
The healthcare domain is characterized by heterogeneous data modalities, such as imaging and physiological data. In practice, the variety of medical data assists clinicians in deci…
Multi-Label Generalized Zero Shot Learning for the Classification of Disease in Chest Radiographs
Nasir Hayat, Hazem Lashen, Farah E. Shamout
Despite the success of deep neural networks in chest X-ray (CXR) diagnosis, supervised learning only allows the prediction of disease classes that were seen during training. At inf…
Clinical prediction system of complications among COVID-19 patients: a development and validation retrospective multicentre study
Ghadeer O. Ghosheh, Bana Alamad, Kai-Wen Yang +10
Existing prognostic tools mainly focus on predicting the risk of mortality among patients with coronavirus disease 2019. However, clinical evidence suggests that COVID-19 can resul…