activity
20172022
most citedPathologyBERT -- Pre-trained Vs. A New Transformer Language Model for Pathology Domain

9 citations · 16 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20229 cited

PathologyBERT -- Pre-trained Vs. A New Transformer Language Model for Pathology Domain

Thiago Santos, Amara Tariq, Susmita Das +4

Pathology text mining is a challenging task given the reporting variability and constant new findings in cancer sub-type definitions. However, successful text mining of a large pat…

cs.CV2020

Generalization of Deep Convolutional Neural Networks -- A Case-study on Open-source Chest Radiographs

Nazanin Mashhaditafreshi, Amara Tariq, Judy Wawira Gichoya +1

Deep Convolutional Neural Networks (DCNNs) have attracted extensive attention and been applied in many areas, including medical image analysis and clinical diagnosis. One major cha…

eess.IV20205 cited

Was there COVID-19 back in 2012? Challenge for AI in Diagnosis with Similar Indications

Imon Banerjee, Priyanshu Sinha, Saptarshi Purkayastha +5

Purpose: Since the recent COVID-19 outbreak, there has been an avalanche of research papers applying deep learning based image processing to chest radiographs for detection of the…

cs.CV20172 cited

Learning Semantics for Image Annotation

Amara Tariq, Hassan Foroosh

Image search and retrieval engines rely heavily on textual annotation in order to match word queries to a set of candidate images. A system that can automatically annotate images w…

cs.CV2017

Image Annotation using Multi-Layer Sparse Coding

Amara Tariq, Hassan Foroosh

Automatic annotation of images with descriptive words is a challenging problem with vast applications in the areas of image search and retrieval. This problem can be viewed as a la…