[Retracted] Global Increase in Breast Cancer Incidence: Risk Factors and Preventive Measures

D Kashyap, D Pal, R Sharma, VK Garg… - BioMed research …, 2022 - Wiley Online Library
Breast cancer is a global cause for concern owing to its high incidence around the world.
The alarming increase in breast cancer cases emphasizes the management of disease at …

A study of CNN and transfer learning in medical imaging: Advantages, challenges, future scope

AW Salehi, S Khan, G Gupta, BI Alabduallah, A Almjally… - Sustainability, 2023 - mdpi.com
This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and
transfer learning in the context of medical imaging. Medical imaging plays a critical role in …

Incremental learning-based cascaded model for detection and localization of tuberculosis from chest x-ray images

S Vats, V Sharma, K Singh, A Katti, MM Ariffin… - Expert Systems with …, 2024 - Elsevier
Rapid treatment protocols such as X-ray and CT scans have played a crucial role in the
diagnosis of tuberculosis (TB infection). Automatic detection of CXR is required to speed up …

Automated multi-class classification of lung diseases from CXR-images using pre-trained convolutional neural networks

SH Karaddi, LD Sharma - Expert Systems with Applications, 2023 - Elsevier
Abstract According to the World Health Organization (WHO), Pneumonia, COVID-19,
Tuberculosis, and Pneumothorax are the leading death causes in the world. Coughing …

Role of artificial intelligence in COVID-19 detection

A Gudigar, U Raghavendra, S Nayak, CP Ooi… - Sensors, 2021 - mdpi.com
The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …

CO-IRv2: Optimized InceptionResNetV2 for COVID-19 detection from chest CT images

MRH Mondal, S Bharati, P Podder - PloS one, 2021 - journals.plos.org
This paper focuses on the application of deep learning (DL) in the diagnosis of coronavirus
disease (COVID-19). The novelty of this work is in the introduction of optimized …

SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19

KK Patro, JP Allam, M Hammad, R Tadeusiewicz… - Biocybernetics and …, 2023 - Elsevier
Abstract Background and Objective The global population has been heavily impacted by the
COVID-19 pandemic of coronavirus. Infections are spreading quickly around the world, and …

A comparative study of detecting covid 19 by using chest X-ray images–A deep learning approach

J Miah, RH Khan, S Ahmed… - 2023 IEEE World AI IoT …, 2023 - ieeexplore.ieee.org
SARS-CoV-2's COVID-19 pandemic has quickly spread over the world, inflicting a sizable
number of illnesses and fatalities. Stopping the virus's spread depends on correctly and …

Ensemble image explainable AI (XAI) algorithm for severe community-acquired pneumonia and COVID-19 respiratory infections

L Zou, HL Goh, CJY Liew, JL Quah… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Since the onset of the COVID-19 pandemic in 2019, many clinical prognostic scoring tools
have been proposed or developed to aid clinicians in the disposition and severity …

Effect of image transformation on EfficientNet model for COVID-19 CT image classification

AS Ebenezer, SD Kanmani, M Sivakumar… - Materials Today …, 2022 - Elsevier
Abstract The Novel Corona Virus 2019 has drastically affected millions of people all around
the world and was a huge threat to the human race since its evolution in 2019. Chest CT …