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Contrastive Self-Supervised Ensemble Transfer Learning for Robust Skin Cancer Classification and Early Detection. [PDF]

Asian Pac J Cancer Prev
Mohammed AS, Mohammed Ali MS, Mohammed Jihad Abdalwahid S, Wahhab Kareem S.   +3 more
europepmc   +1 more source

Optimizing breast cancer classification based on cat swarm-enhanced ensemble neural network approach for improved diagnosis and treatment decisions. [PDF]

Sci Rep
Hayum AA, Daniel Shadrach F.
europepmc   +1 more source

Multi-Scale Vision Transformer with Optimized Feature Fusion for Mammographic Breast Cancer Classification. [PDF]

Diagnostics (Basel)
Ahmed S, Elazab N, El-Gayar MM, Elmogy M, Fouda YM.   +4 more
europepmc   +1 more source

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Dermatological Cancer Classification

2025 International Conference on Emerging Trends in Industry 4.0 Technologies (ICETI4T)
Early and accurate detection of skin cancer is critical for effective treatment and improved patient outcomes. In this study, we develop and evaluate deep learning models, including DermaNet, ResNet50, EfficientNetB0, and a hybrid CNN, for dermatological
Pratish Khurdamoje, Siddhesh Chavan, Piyush Parekh, Aditya Pathak, Jyoti Bansode, Vaishali Korade   +5 more
semanticscholar   +2 more sources

The three dimensional dosimetry imaging for automated eye cancer classification using transfer learning model

International Conference on Computing Communication and Networking Technologies, 2023
Computer vision methods utilizing transfer learning can offer a promising approach for automated eye cancer diagnosis with three-dimensional dosimetry imaging.
Murtuza Ali Mohammed, Vazeer Ali Mohammed, Rakesh Ramakrishnan, Mehmood Ali Mohammed, J. Logeshwaran, M. S.   +5 more
semanticscholar   +1 more source

An Attention-Based Mechanism to Combine Images and Metadata in Deep Learning Models Applied to Skin Cancer Classification

IEEE journal of biomedical and health informatics, 2021
Computer-aided skin cancer classification systems built with deep neural networks usually yield predictions based only on images of skin lesions. Despite presenting promising results, it is possible to achieve higher performance by taking into account ...
André G. C. Pacheco, R. Krohling
semanticscholar   +1 more source

A Deep Learning Method for Breast Cancer Classification in the Pathology Images

IEEE journal of biomedical and health informatics, 2022
Objective: Breast cancer is the most common female cancer in the world, and it poses a huge threat to women's health. There is currently promising research concerning its early diagnosis using deep learning methodologies.
Min Liu, Lanlan Hu, Ying Tang, Chu Wang, Yu He, Chunyan Zeng, Kun Lin, Zhizi He, Wujie Huo   +8 more
semanticscholar   +1 more source

A Hybrid Framework for Lung Cancer Classification

Electronics, 2022
Cancer is the second leading cause of death worldwide, and the death rate of lung cancer is much higher than other types of cancers. In recent years, numerous novel computer-aided diagnostic techniques with deep learning have been designed to detect lung
Zeyu Ren, Yudong Zhang, Shuihua Wang
semanticscholar   +1 more source

Skin Cancer Classification

2023
Skin cancer is a common and dangerous form of cancer. This is a dangerous kind of cancer, and early detection is crucial for successful treatment. Malignant tumors develop when healthy, normal skin cells experience genetic alterations and begin to grow uncontrolled. An important risk factor for skin cancer is ultraviolet (UV) radiation from the sun and
Nikita Mali, Prajwal Thawari, Uday Jawheri, Sulaxan Jadhav   +3 more
openaire   +1 more source

A Systematic Method for Breast Cancer Classification using RFE Feature Selection

2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2022
Breast cancer is among leading reasons for the deaths of women globally. Machine learning techniques can help to classify breast cancer based on some features.
Ravi Kumar Sachdeva, Priyanka Bathla, P. Rani, Vinay Kukreja, Rakesh Ahuja   +4 more
semanticscholar   +1 more source