[HTML][HTML] A comprehensive survey of deep learning in the field of medical imaging and medical natural language processing: Challenges and research directions

B Pandey, DK Pandey, BP Mishra… - Journal of King Saud …, 2022 - Elsevier
The extensive growth of data in the health domain has increased the utility of Deep Learning
in health. Deep learning is a highly advanced successor of artificial neural networks, having …

Cluster-to-conquer: A framework for end-to-end multi-instance learning for whole slide image classification

Y Sharma, A Shrivastava, L Ehsan… - … Imaging with Deep …, 2021 - proceedings.mlr.press
In recent years, the availability of digitized Whole Slide Images (WSIs) has enabled the use
of deep learning-based computer vision techniques for automated disease diagnosis …

Automated detection of celiac disease using Machine Learning Algorithms

CA Stoleru, EH Dulf, L Ciobanu - Scientific reports, 2022 - nature.com
Celiac disease is a disorder of the immune system that mainly affects the small intestine but
can also affect the skeletal system. The diagnosis relies on histological assessment of …

Automated interpretation of biopsy images for the detection of celiac disease using a machine learning approach

JEW Koh, S De Michele, VK Sudarshan… - Computer Methods and …, 2021 - Elsevier
Background and objectives Celiac disease is an autoimmune disease occurring in about 1
in 100 people worldwide. Early diagnosis and efficient treatment are crucial in mitigating the …

Self-attentive adversarial stain normalization

A Shrivastava, W Adorno, Y Sharma, L Ehsan… - … and Challenges: Virtual …, 2021 - Springer
Abstract Hematoxylin and Eosin (H&E) stained Whole Slide Images (WSIs) are utilized for
biopsy visualization-based diagnostic and prognostic assessment of diseases. Variation in …

Neural network methods for diagnosing patient conditions from cardiopulmonary exercise testing data

DE Brown, S Sharma, JA Jablonski, A Weltman - BioData Mining, 2022 - Springer
Background Cardiopulmonary exercise testing (CPET) provides a reliable and reproducible
approach to measuring fitness in patients and diagnosing their health problems. However …

Heterogeneous integration of in-memory analog computing architectures with tensor processing units

ME Elbtity, B Reidy, MH Amin, R Zand - Proceedings of the Great Lakes …, 2023 - dl.acm.org
Tensor processing units (TPUs), specialized hardware accelerators for machine learning
tasks, have shown significant performance improvements when executing convolutional …

Artificial intelligence-based analytics for diagnosis of small bowel enteropathies and black box feature detection

S Syed, L Ehsan, A Shrivastava… - Journal of pediatric …, 2021 - journals.lww.com
Objectives: Striking histopathological overlap between distinct but related conditions poses
a disease diagnostic challenge. There is a major clinical need to develop computational …

Automated classification of celiac disease in histopathological images: a multi-scale approach

S Püttmann, LB Ferris, N Marini… - Medical Imaging …, 2024 - spiedigitallibrary.org
With a prevalence of 1-2% Celiac Disease (CD) is one of the most commonly known genetic
and autoimmune diseases, which is induced by the intake of gluten in genetically …

Clustering-Based Cancer Diagnosis Model for Whole Slide Image

TS Sheikh, J Shim, M Cho - Proceedings of the 2023 8th International …, 2023 - dl.acm.org
Automated classification of Whole Slide Images (WSIs) is of great significance for early
diagnosis of cancer. Existing approaches are trained on a specific level which affects the …