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 …
Radiomics in breast cancer classification and prediction
Breast Cancer (BC) is the common form of cancer in women. Its diagnosis and screening are
usually performed through different imaging modalities such as mammography, magnetic …
usually performed through different imaging modalities such as mammography, magnetic …
Deep learning for image-based cancer detection and diagnosis− A survey
In this paper, we aim to provide a survey on the applications of deep learning for cancer
detection and diagnosis and hope to provide an overview of the progress in this field. In the …
detection and diagnosis and hope to provide an overview of the progress in this field. In the …
[HTML][HTML] Machine learning methods for quantitative radiomic biomarkers
Radiomics extracts and mines large number of medical imaging features quantifying tumor
phenotypic characteristics. Highly accurate and reliable machine-learning approaches can …
phenotypic characteristics. Highly accurate and reliable machine-learning approaches can …
Radiomics and deep learning in lung cancer
Lung malignancies have been extensively characterized through radiomics and deep
learning. By providing a three-dimensional characterization of the lesion, models based on …
learning. By providing a three-dimensional characterization of the lesion, models based on …
[HTML][HTML] Radiomics and artificial intelligence for precision medicine in lung cancer treatment
Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …
Medical Internet of things using machine learning algorithms for lung cancer detection
This paper empirically evaluates the several machine learning algorithms adaptable for lung
cancer detection linked with IoT devices. In this work, a review of nearly 65 papers for …
cancer detection linked with IoT devices. In this work, a review of nearly 65 papers for …
Radiomic machine-learning classifiers for prognostic biomarkers of head and neck cancer
Introduction “Radiomics” extracts and mines a large number of medical imaging features in a
non-invasive and cost-effective way. The underlying assumption of radiomics is that these …
non-invasive and cost-effective way. The underlying assumption of radiomics is that these …
[HTML][HTML] The role of deep learning and radiomic feature extraction in cancer-specific predictive modelling: a review
This paper reviews objective methods for prognostic modelling of cancer tumours located
within radiology images, a process known as radiomics. Radiomics is a novel feature …
within radiology images, a process known as radiomics. Radiomics is a novel feature …
Convolution neural networks for diagnosing colon and lung cancer histopathological images
S Mangal, A Chaurasia, A Khajanchi - arXiv preprint arXiv:2009.03878, 2020 - arxiv.org
Lung and Colon cancer are one of the leading causes of mortality and morbidity in adults.
Histopathological diagnosis is one of the key components to discern cancer type. The aim of …
Histopathological diagnosis is one of the key components to discern cancer type. The aim of …