Multimodal machine learning in precision health: A scoping review
Abstract Machine learning is frequently being leveraged to tackle problems in the health
sector including utilization for clinical decision-support. Its use has historically been focused …
sector including utilization for clinical decision-support. Its use has historically been focused …
Designing deep learning studies in cancer diagnostics
A Kleppe, OJ Skrede, S De Raedt, K Liestøl… - Nature Reviews …, 2021 - nature.com
The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …
and systems are frequently claimed to perform comparable with or better than clinicians …
Improved breast cancer classification through combining graph convolutional network and convolutional neural network
Aim In a pilot study to improve detection of malignant lesions in breast mammograms, we
aimed to develop a new method called BDR-CNN-GCN, combining two advanced neural …
aimed to develop a new method called BDR-CNN-GCN, combining two advanced neural …
Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor …
Background: in current clinical practice, the standard evaluation for axillary lymph node
(ALN) status in breast cancer has a low efficiency and is based on an invasive procedure …
(ALN) status in breast cancer has a low efficiency and is based on an invasive procedure …
[HTML][HTML] Application of deep learning in breast cancer imaging
This review gives an overview of the current state of deep learning research in breast cancer
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …
Development and validation of a preoperative magnetic resonance imaging radiomics–based signature to predict axillary lymph node metastasis and disease-free …
Importance Axillary lymph node metastasis (ALNM) status, typically estimated using an
invasive procedure with a high false-negative rate, strongly affects the prognosis of …
invasive procedure with a high false-negative rate, strongly affects the prognosis of …
Artificial intelligence in ultrasound
YT Shen, L Chen, WW Yue, HX Xu - European Journal of Radiology, 2021 - Elsevier
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Elsevier logo Journals & Books Search RegisterSign in View PDF Download full issue …
Elsevier logo Journals & Books Search RegisterSign in View PDF Download full issue …
[HTML][HTML] Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization
Over the last decade there has been an extensive evolution in the Artificial Intelligence (AI)
field. Modern radiation oncology is based on the exploitation of advanced computational …
field. Modern radiation oncology is based on the exploitation of advanced computational …
Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy
This brief review summarizes the major applications of artificial intelligence (AI), in particular
deep learning approaches, in molecular imaging and radiation therapy research. To this …
deep learning approaches, in molecular imaging and radiation therapy research. To this …
Systematic review of computing approaches for breast cancer detection based computer aided diagnosis using mammogram images
DA Zebari, DA Ibrahim, DQ Zeebaree… - Applied Artificial …, 2021 - Taylor & Francis
Breast cancer is one of the most prevalent types of cancer that plagues females. Mortality
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …