activity
20192021
most citedHMIC: Hierarchical Medical Image Classification, A Deep Learning Approach

65 citations · 67 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV2021★ 2 cited

Advancing Eosinophilic Esophagitis Diagnosis and Phenotype Assessment with Deep Learning Computer Vision

William Adorno, Alexis Catalano, Lubaina Ehsan +5

Eosinophilic Esophagitis (EoE) is an inflammatory esophageal disease which is increasing in prevalence. The diagnostic gold-standard involves manual review of a patient's biopsy ti…

eess.IV2020

Hand-drawn Symbol Recognition of Surgical Flowsheet Graphs with Deep Image Segmentation

William Adorno, Angela Yi, Marcel Durieux +1

Perioperative data are essential to investigating the causes of adverse surgical outcomes. In some low to middle income countries, these data are computationally inaccessible due t…

eess.IV2020★ 65 cited

HMIC: Hierarchical Medical Image Classification, A Deep Learning Approach

Kamran Kowsari, Rasoul Sali, Lubaina Ehsan +7

Image classification is central to the big data revolution in medicine. Improved information processing methods for diagnosis and classification of digital medical images have show…

eess.IV2019

Self-Attentive Adversarial Stain Normalization

Aman Shrivastava, Will Adorno, Yash Sharma +7

Hematoxylin and Eosin (H&E) stained Whole Slide Images (WSIs) are utilized for biopsy visualization-based diagnostic and prognostic assessment of diseases. Variation in the H&E sta…

eess.IV2019

Diagnosis of Celiac Disease and Environmental Enteropathy on Biopsy Images Using Color Balancing on Convolutional Neural Networks

Kamran Kowsari, Rasoul Sali, Marium N. Khan +7

Celiac Disease (CD) and Environmental Enteropathy (EE) are common causes of malnutrition and adversely impact normal childhood development. CD is an autoimmune disorder that is pre…