Deep learning based HEp-2 image classification: A comprehensive review

S Rahman, L Wang, C Sun, L Zhou - Medical Image Analysis, 2020 - Elsevier
Classification of HEp-2 cell patterns plays a significant role in the indirect
immunofluorescence test for identifying autoimmune diseases in the human body. Many …

mACPpred: a support vector machine-based meta-predictor for identification of anticancer peptides

V Boopathi, S Subramaniyam, A Malik, G Lee… - International journal of …, 2019 - mdpi.com
Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer
cells. The accurate prediction of ACPs from given peptide sequences remains as an open …

Performance of fine-tuning convolutional neural networks for HEP-2 image classification

V Taormina, D Cascio, L Abbene, G Raso - Applied Sciences, 2020 - mdpi.com
The search for anti-nucleus antibodies (ANA) represents a fundamental step in the
diagnosis of autoimmune diseases. The test considered the gold standard for ANA research …

Deep convolutional neural network for HEp-2 fluorescence intensity classification

D Cascio, V Taormina, G Raso - Applied Sciences, 2019 - mdpi.com
Featured Application In this paper we describe an automatic system for fluorescence
intensity classification to support the autoimmune diagnostics in HEp-2 image analysis. The …

Deep active learning for automatic mitotic cell detection on HEp-2 specimen medical images

A Anaam, MA Al-Antari, J Hussain, N Abdel Samee… - Diagnostics, 2023 - mdpi.com
Identifying Human Epithelial Type 2 (HEp-2) mitotic cells is a crucial procedure in anti-
nuclear antibodies (ANAs) testing, which is the standard protocol for detecting connective …

Deep CNN for IIF images classification in autoimmune diagnostics

D Cascio, V Taormina, G Raso - Applied Sciences, 2019 - mdpi.com
The diagnosis and monitoring of autoimmune diseases are very important problem in
medicine. The most used test for this purpose is the antinuclear antibody (ANA) test. An …

Application of supervised machine learning to recognize competent level and mixed antinuclear antibody patterns based on ICAP international consensus

YD Wu, RK Sheu, CW Chung, YC Wu, CC Ou… - Diagnostics, 2021 - mdpi.com
Background: Antinuclear antibody pattern recognition is vital for autoimmune disease
diagnosis but labor-intensive for manual interpretation. To develop an automated pattern …

Sedimentation of halloysite nanotubes from different deposits in aqueous media at variable ionic strengths

G Cavallaro, G Lazzara, V Taormina… - Colloids and Surfaces A …, 2019 - Elsevier
Halloysite clay is a natural nanomaterial that is attracting a growing interest in colloidal
science. The halloysite aqueous dispersion stability is a key aspect for the configuration of a …

[PDF][PDF] Application of the deep convolutional neural network for the classification of auto immune diseases

F Muhammad, J Khan, A Ullah, F Ullah… - CMC-Comput Mater …, 2023 - cdn.techscience.cn
ABSTRACT IIF (Indirect Immune Florescence) has gained much attention recently due to its
importance in medical sciences. The primary purpose of this work is to highlight a step-by …

Identification of HEp-2 specimen images with mitotic cell patterns

K Gupta, A Bhavsar, AK Sao - Biocybernetics and Biomedical Engineering, 2020 - Elsevier
In this paper, we propose and analyze a novel framework to identify the HEp-2 specimen
images, consisting of mitotic spindle (MS) pattern cells. It is based on the fact that the cells …