[HTML][HTML] Data augmentation: A comprehensive survey of modern approaches

A Mumuni, F Mumuni - Array, 2022 - Elsevier
To ensure good performance, modern machine learning models typically require large
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …

[HTML][HTML] Public covid-19 x-ray datasets and their impact on model bias–a systematic review of a significant problem

BG Santa Cruz, MN Bossa, J Sölter, AD Husch - Medical image analysis, 2021 - Elsevier
Computer-aided-diagnosis and stratification of COVID-19 based on chest X-ray suffers from
weak bias assessment and limited quality-control. Undetected bias induced by inappropriate …

Handling class imbalance in COVID-19 chest X-ray images classification: Using SMOTE and weighted loss

E Chamseddine, N Mansouri, M Soui, M Abed - Applied Soft Computing, 2022 - Elsevier
Healthcare systems worldwide have been struggling since the beginning of the COVID-19
pandemic. The early diagnosis of this unprecedented infection has become their ultimate …

[HTML][HTML] Enhanced performance of Dark-Nets for brain tumor classification and segmentation using colormap-based superpixel techniques

S Ahuja, BK Panigrahi, TK Gandhi - Machine Learning with Applications, 2022 - Elsevier
The brain tumor is the deadliest disease in adults as it arises due to an abnormal mass of
cells that grows rapidly and it alters the proper functioning of the organs. In clinical practice …

Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study

M Nishio, D Kobayashi, E Nishioka, H Matsuo… - Scientific Reports, 2022 - nature.com
This retrospective study aimed to develop and validate a deep learning model for the
classification of coronavirus disease-2019 (COVID-19) pneumonia, non-COVID-19 …

Ensembles of convolutional neural network models for pediatric pneumonia diagnosis

H Liz, M Sánchez-Montañés, A Tagarro… - Future Generation …, 2021 - Elsevier
Pneumonia is a lung infection that causes 15% of childhood mortality (under 5 years old),
over 800,000 children under five every year, around 2,200 every day, all over the world. This …

Covid-19 detection: A systematic review of machine and deep learning-based approaches utilizing chest x-rays and ct scans

KR Bhatele, A Jha, D Tiwari, M Bhatele, S Sharma… - Cognitive …, 2024 - Springer
This review study presents the state-of-the-art machine and deep learning-based COVID-19
detection approaches utilizing the chest X-rays or computed tomography (CT) scans. This …

[HTML][HTML] A Deep learning based data augmentation method to improve COVID-19 detection from medical imaging

DR Beddiar, M Oussalah, U Muhammad… - Knowledge-Based …, 2023 - Elsevier
The worldwide spread of the Coronavirus pandemic and its huge impact challenged medical
and research communities to explore novel approaches for medical diagnosis from medical …

A deep learning review of resnet architecture for lung disease Identification in CXR Image

SA Hasanah, AA Pravitasari, AS Abdullah, IN Yulita… - Applied Sciences, 2023 - mdpi.com
The lungs are two of the most crucial organs in the human body because they are connected
to the respiratory and circulatory systems. Lung cancer, COVID-19, pneumonia, and other …

MNet-10: A robust shallow convolutional neural network model performing ablation study on medical images assessing the effectiveness of applying optimal data …

S Montaha, S Azam, AKMRH Rafid, MZ Hasan… - Frontiers in …, 2022 - frontiersin.org
Interpretation of medical images with a computer-aided diagnosis (CAD) system is arduous
because of the complex structure of cancerous lesions in different imaging modalities, high …