Publications | aetherAI

Super - Charging Digital Pathology AI

Digital pathology is currently experiencing a tectonic shift. The adoption of digital pathology had been slow because the return on investment was unclear. The advent of deep neural networks (DNNs), the core technology of this current wave of artificial intelligence, with its superlative performance at image-recognition tasks, is rapidly changing this perception and stirring up unprecedented interest in digital pathology.

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Published Journal Articles

Oct 27, 2021

aetherAI’s Machine Learning Approach for T-cell Lymphomas Diagnosis Support published in Cancers

Published by Cancers, Oct. 2021 aetherAI presented a machine learning approach for accurate quantification of nuclear morphometrics and...

Sep 20, 2021

Glomerular disease classification and lesion identification by machine learning

Published by Biomedical Journal, Sept. 2021 Abstract Background Classification of glomerular diseases and identification of glomerular...

Sep 14, 2021

Stain Mix-Up: Unsupervised Domain Generalization for Histopathology Images

Published by MICCAI2021, Sept. 2021 Abstract Computational histopathology studies have shown that stain color variations considerably...

Sep 4, 2021

Hybrid Aggregation Network for Survival Analysis from Whole Slide Histopathological Images

Published by MICCAI2021, Sept. 2021 Abstract Understanding of prognosis and mortality is crucial for evaluating the treatment plans for...

Jun 7, 2021

Identification of nodal micrometastasis in colorectal cancer by deep learning on annotation-free WSI

Published by Modern Pathology, June 2021 Abstract Detection of nodal micrometastasis (tumor size: 0.2–2.0 mm) is challenging for...

Mar 11, 2021

Deep learning approach for automatic landmark detection in whole-spine lateral radiographs

Published by Scientific Report, April 2021 Deep learning approach for automatic landmark detection and alignment analysis in whole-spine...

Feb 11, 2021

Artificial Intelligence–Based Screening for Mycobacteria in Whole-Slide Images of Tissue Samples

Published by American Journal of Clinical Pathology, Feb. 2021 Abstract Objectives This study aimed to develop and validate a deep...

Feb 4, 2021

An annotation-free whole-slide training approach to pathological classification of lung cancer types

Published by Nature Communications, Feb. 2021 Abstract Deep learning for digital pathology is hindered by the extremely high spatial...

Jan 14, 2021

aetherAI's new article publishing in Annals of Translational Medicine

Published by Annals of Translational Medicine, Jan. 2021 Predicting aggressive histopathological features in esophageal cancer with...

Feb 9, 2020

Successful Identification of Nasopharyngeal Carcinoma in Nasopharyngeal Biopsies Using Deep Learning

Published by Cancers, Feb. 2020 Abstract Pathologic diagnosis of nasopharyngeal carcinoma (NPC) can be challenging since most cases are...

Jun 30, 2019

Deep Convolutional Neural Network-Based Positron Emission Tomography Analysis Predicts Esophageal Ca

Published by Journal of Clinical Medicine on 13 June 2019 Abstract In esophageal cancer, few prediction tools can be confidently used in...