Recent advancement in cancer diagnosis using machine learning and deep learning techniques: A comprehensive review
Being a second most cause of mortality worldwide, cancer has been identified as a perilous
disease for human beings, where advance stage diagnosis may not help much in …
disease for human beings, where advance stage diagnosis may not help much in …
[HTML][HTML] Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges
T Saba - Journal of infection and public health, 2020 - Elsevier
Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture
Brain tumor is one of the most dreadful natures of cancer and caused a huge number of
deaths among kids and adults from the past few years. According to WHO standard, the …
deaths among kids and adults from the past few years. According to WHO standard, the …
Brain tumor segmentation using K‐means clustering and deep learning with synthetic data augmentation for classification
Image processing plays a major role in neurologists' clinical diagnosis in the medical field.
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Brain tumor detection and multi‐classification using advanced deep learning techniques
A brain tumor is an uncontrolled development of brain cells in brain cancer if not detected at
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
The state of the art of deep learning models in medical science and their challenges
With time, AI technologies have matured well and resonated in various domains of applied
sciences and engineering. The sub-domains of AI, machine learning (ML), deep learning …
sciences and engineering. The sub-domains of AI, machine learning (ML), deep learning …
RETRACTED ARTICLE: Peripheral Blood Smear Images Classification for Acute Lymphoblastic Leukemia Diagnosis with an Improved Convolutional Neural Network
E Özbay, FA Özbay, FS Gharehchopogh - Journal of Bionic Engineering, 2023 - Springer
The Editor-in-Chief has retracted this article because it overlaps significantly with a prior
publication with no common authors [1]. Specifically, images in Figs. 3 and 4 appear highly …
publication with no common authors [1]. Specifically, images in Figs. 3 and 4 appear highly …
Deep learning in cancer diagnosis and prognosis prediction: a minireview on challenges, recent trends, and future directions
Deep learning (DL) is a branch of machine learning and artificial intelligence that has been
applied to many areas in different domains such as health care and drug design. Cancer …
applied to many areas in different domains such as health care and drug design. Cancer …
Brain tumor detection and classification: A framework of marker‐based watershed algorithm and multilevel priority features selection
Brain tumor identification using magnetic resonance images (MRI) is an important research
domain in the field of medical imaging. Use of computerized techniques helps the doctors for …
domain in the field of medical imaging. Use of computerized techniques helps the doctors for …
Comparison of traditional image processing and deep learning approaches for classification of white blood cells in peripheral blood smear images
Automated classification and morphological analysis of white blood cells has been
addressed since last four decades, but there is no optimal method which can be used as …
addressed since last four decades, but there is no optimal method which can be used as …