A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning

S Atasever, N Azginoglu, DS Terzi, R Terzi - Clinical imaging, 2023 - Elsevier
This survey aims to identify commonly used methods, datasets, future trends, knowledge
gaps, constraints, and limitations in the field to provide an overview of current solutions used …

[Retracted] Ant Colony Optimization‐Enabled CNN Deep Learning Technique for Accurate Detection of Cervical Cancer

R Kavitha, DK Jothi, K Saravanan… - BioMed Research …, 2023 - Wiley Online Library
Cancer is characterized by abnormal cell growth and proliferation, which are both diagnostic
indicators of the disease. When cancerous cells enter one organ, there is a risk that they …

Diagnosis of cervical cancer based on ensemble deep learning network using colposcopy images

V Chandran, MG Sumithra, A Karthick… - BioMed Research …, 2021 - Wiley Online Library
Traditional screening of cervical cancer type classification majorly depends on the
pathologist's experience, which also has less accuracy. Colposcopy is a critical component …

Recent advancement in cervical cancer diagnosis for automated screening: a detailed review

B Chitra, SS Kumar - Journal of Ambient Intelligence and Humanized …, 2022 - Springer
Cervical cancer is one of the most common and dangerous diseases for women. Initial
diagnosis and classification of cervical cancer are to reduce the mortality rate. The Pap …

Cervical cancer diagnostics healthcare system using hybrid object detection adversarial networks

R Elakkiya, V Subramaniyaswamy… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Cervical cancer is one of the common cancers among women and it causes significant
mortality in many developing countries. Diagnosis of cervical lesions is done using pap …

Integrating convolutional neural networks, kNN, and Bayesian optimization for efficient diagnosis of Alzheimer's disease in magnetic resonance images

S Lahmiri - Biomedical Signal Processing and Control, 2023 - Elsevier
Deep learning is attracting growing interest from biomedical engineering community.
Researchers and clinicians are also increasingly interested in development of machine …

[HTML][HTML] Improving prediction of cervical cancer using knn imputed smote features and multi-model ensemble learning approach

H Karamti, R Alharthi, AA Anizi, RM Alhebshi… - Cancers, 2023 - mdpi.com
Simple Summary This paper presents a cervical cancer detection approach where the KNN
Imputer techniques is used to fill the missing values and after that SMOTE upsampled …

Cervical cancer diagnosis using very deep networks over different activation functions

KMA Adweb, N Cavus, B Sekeroglu - Ieee Access, 2021 - ieeexplore.ieee.org
Cancer prevention is mainly achieved by screening the transformation zones. Cervical pre-
cancerous stages can be seen in three different types, and all can transform into cancer …

MLNet: metaheuristics-based lightweight deep learning network for cervical cancer diagnosis

M Kaur, D Singh, V Kumar… - IEEE journal of biomedical …, 2022 - ieeexplore.ieee.org
One of the leading causes of cancer-related deaths among women is cervical cancer. Early
diagnosis and treatment can minimize the complications of this cancer. Recently …

Cervical transformation zone segmentation and classification based on improved inception-resnet-v2 using colposcopy images

S Dash, PK Sethy, SK Behera - Cancer Informatics, 2023 - journals.sagepub.com
The second most frequent malignancy in women worldwide is cervical cancer. In the
transformation (transitional) zone, which is a region of the cervix, columnar cells are …