Cancer diagnosis using deep learning: a bibliographic review
In this paper, we first describe the basics of the field of cancer diagnosis, which includes
steps of cancer diagnosis followed by the typical classification methods used by doctors …
steps of cancer diagnosis followed by the typical classification methods used by doctors …
Skin cancer detection using non-invasive techniques
V Narayanamurthy, P Padmapriya, A Noorasafrin… - RSC …, 2018 - pubs.rsc.org
Skin cancer is the most common form of cancer and is globally rising. Historically, the
diagnosis of skin cancers has depended on various conventional techniques which are of …
diagnosis of skin cancers has depended on various conventional techniques which are of …
Classification of skin disease using deep learning neural networks with MobileNet V2 and LSTM
PN Srinivasu, JG SivaSai, MF Ijaz, AK Bhoi, W Kim… - Sensors, 2021 - mdpi.com
Deep learning models are efficient in learning the features that assist in understanding
complex patterns precisely. This study proposed a computerized process of classifying skin …
complex patterns precisely. This study proposed a computerized process of classifying skin …
[HTML][HTML] Fine-tuned DenseNet-169 for breast cancer metastasis prediction using FastAI and 1-cycle policy
Lymph node metastasis in breast cancer may be accurately predicted using a DenseNet-
169 model. However, the current system for identifying metastases in a lymph node is …
169 model. However, the current system for identifying metastases in a lymph node is …
An internet of health things‐driven deep learning framework for detection and classification of skin cancer using transfer learning
Abstract As specified by World Health Organization, the occurrence of skin cancer has been
growing over the past decades. At present, 2 to 3 million nonmelanoma skin cancers and …
growing over the past decades. At present, 2 to 3 million nonmelanoma skin cancers and …
Multiclass skin lesion classification using a novel lightweight deep learning framework for smart healthcare
L Hoang, SH Lee, EJ Lee, KR Kwon - Applied Sciences, 2022 - mdpi.com
Skin lesion classification has recently attracted significant attention. Regularly, physicians
take much time to analyze the skin lesions because of the high similarity between these skin …
take much time to analyze the skin lesions because of the high similarity between these skin …
Eff2Net: An efficient channel attention-based convolutional neural network for skin disease classification
R Karthik, TS Vaichole, SK Kulkarni, O Yadav… - … Signal Processing and …, 2022 - Elsevier
The primary layer of protection for vital organs in the human body is the skin. It functions as a
barrier to protect our internal organs from different sources. However, infections caused by …
barrier to protect our internal organs from different sources. However, infections caused by …
Diagnosis of skin cancer using machine learning techniques
A Murugan, SAH Nair, AAP Preethi… - Microprocessors and …, 2021 - Elsevier
Generally, skin disease is a common one in human diseases. In computer vision application,
the skin color is the powerful indication for this disease. This system identifies the skin …
the skin color is the powerful indication for this disease. This system identifies the skin …
An expert system for selecting wart treatment method
As benign tumors, warts are made through the mediation of Human Papillomavirus (HPV)
and may grow on all parts of body, especially hands and feet. There are several treatment …
and may grow on all parts of body, especially hands and feet. There are several treatment …
Skin disease recognition method based on image color and texture features
L Wei, Q Gan, T Ji - Computational and mathematical methods …, 2018 - Wiley Online Library
Skin diseases have a serious impact on people's life and health. Current research proposes
an efficient approach to identify singular type of skin diseases. It is necessary to develop …
an efficient approach to identify singular type of skin diseases. It is necessary to develop …