Transfer learning for medical image classification: a literature review
HE Kim, A Cosa-Linan, N Santhanam, M Jannesari… - BMC medical …, 2022 - Springer
Background Transfer learning (TL) with convolutional neural networks aims to improve
performances on a new task by leveraging the knowledge of similar tasks learned in …
performances on a new task by leveraging the knowledge of similar tasks learned in …
Artificial intelligence and machine learning for medical imaging: A technology review
Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …
of disruptive technical advances and impressive experimental results, notably in the field of …
Stochastic dilated residual ghost model for breast cancer detection
R Kashyap - Journal of Digital Imaging, 2023 - Springer
One of the most contentious issues in modern medicine is how to effectively standardise
breast cancer screening. Deep learning models are already saving lives in the medical field …
breast cancer screening. Deep learning models are already saving lives in the medical field …
Applications of artificial intelligence and machine learning in smart cities
Smart cities are aimed to efficiently manage growing urbanization, energy consumption,
maintain a green environment, improve the economic and living standards of their citizens …
maintain a green environment, improve the economic and living standards of their citizens …
Deep learning for smart Healthcare—A survey on brain tumor detection from medical imaging
M Arabahmadi, R Farahbakhsh, J Rezazadeh - Sensors, 2022 - mdpi.com
Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …
use of technology in medicine has made significant contributions to human society. In this …
Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks
Coronavirus is an epidemic that spreads very quickly. For this reason, it has very devastating
effects in many areas worldwide. It is vital to detect COVID-19 diseases as quickly as …
effects in many areas worldwide. It is vital to detect COVID-19 diseases as quickly as …
A comprehensive review on breast cancer detection, classification and segmentation using deep learning
The incidence and mortality rate of Breast Cancer (BC) are global problems for women, with
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …
Medical image analysis based on deep learning approach
M Puttagunta, S Ravi - Multimedia tools and applications, 2021 - Springer
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
Ensemble deep-learning-enabled clinical decision support system for breast cancer diagnosis and classification on ultrasound images
Simple Summary In the literature, there exist plenty of research works focused on the
detection and classification of breast cancer. However, only a few works have focused on …
detection and classification of breast cancer. However, only a few works have focused on …
[HTML][HTML] From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare
The medicine and healthcare sector has been evolving and advancing very fast. The
advancement has been initiated and shaped by the applications of data-driven, robust, and …
advancement has been initiated and shaped by the applications of data-driven, robust, and …