A review of deep transfer learning and recent advancements

M Iman, HR Arabnia, K Rasheed - Technologies, 2023 - mdpi.com
Deep learning has been the answer to many machine learning problems during the past two
decades. However, it comes with two significant constraints: dependency on extensive …

Domain adaptation for medical image analysis: a survey

H Guan, M Liu - IEEE Transactions on Biomedical Engineering, 2021 - ieeexplore.ieee.org
Machine learning techniques used in computer-aided medical image analysis usually suffer
from the domain shift problem caused by different distributions between source/reference …

Application of artificial intelligence technology in oncology: Towards the establishment of precision medicine

R Hamamoto, K Suvarna, M Yamada, K Kobayashi… - Cancers, 2020 - mdpi.com
Simple Summary Artificial intelligence (AI) technology has been advancing rapidly in recent
years and is being implemented in society. The medical field is no exception, and the clinical …

A multimodal transformer to fuse images and metadata for skin disease classification

G Cai, Y Zhu, Y Wu, X Jiang, J Ye, D Yang - The Visual Computer, 2023 - Springer
Skin disease cases are rising in prevalence, and the diagnosis of skin diseases is always a
challenging task in the clinic. Utilizing deep learning to diagnose skin diseases could help to …

Universal adversarial attacks on deep neural networks for medical image classification

H Hirano, A Minagi, K Takemoto - BMC medical imaging, 2021 - Springer
Abstract Background Deep neural networks (DNNs) are widely investigated in medical
image classification to achieve automated support for clinical diagnosis. It is necessary to …

New trends in melanoma detection using neural networks: a systematic review

D Popescu, M El-Khatib, H El-Khatib, L Ichim - Sensors, 2022 - mdpi.com
Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health
disease today. The high mortality rate associated with melanoma makes it necessary to …

Skin cancer classification with deep learning: a systematic review

Y Wu, B Chen, A Zeng, D Pan, R Wang… - Frontiers in …, 2022 - frontiersin.org
Skin cancer is one of the most dangerous diseases in the world. Correctly classifying skin
lesions at an early stage could aid clinical decision-making by providing an accurate …

Skin disease diagnosis with deep learning: A review

H Li, Y Pan, J Zhao, L Zhang - Neurocomputing, 2021 - Elsevier
Skin cancer is one of the most threatening diseases worldwide. However, diagnosing skin
cancer correctly is challenging. Recently, deep learning algorithms have emerged to …

Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives

S Kumari, P Singh - Computers in Biology and Medicine, 2024 - Elsevier
Deep learning has demonstrated remarkable performance across various tasks in medical
imaging. However, these approaches primarily focus on supervised learning, assuming that …

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 …