[HTML][HTML] Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges
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 …
Classification of acute lymphoblastic leukemia using deep learning
Acute Leukemia is a life‐threatening disease common both in children and adults that can
lead to death if left untreated. Acute Lymphoblastic Leukemia (ALL) spreads out in children's …
lead to death if left untreated. Acute Lymphoblastic Leukemia (ALL) spreads out in children's …
Microscopic malaria parasitemia diagnosis and grading on benchmark datasets
Malaria parasitemia diagnosis and grading is hard and still far from perfection. Inaccurate
diagnosis and grading has caused tremendous deaths rate particularly in young children …
diagnosis and grading has caused tremendous deaths rate particularly in young children …
Deep learning model integrating features and novel classifiers fusion for brain tumor segmentation
Automatic and precise segmentation and classification of tumor area in medical images is
still a challenging task in medical research. Most of the conventional neural network based …
still a challenging task in medical research. Most of the conventional neural network based …
Automated lung nodule detection and classification based on multiple classifiers voting
Lung cancer is the most common cause of cancer‐related death globally. Currently, lung
nodule detection and classification are performed by radiologist‐assisted computer‐aided …
nodule detection and classification are performed by radiologist‐assisted computer‐aided …
Leukocytes classification and segmentation in microscopic blood smear: a resource-aware healthcare service in smart cities
Smart cities are a future reality for municipalities around the world. Healthcare services play
a vital role in the transformation of traditional cities into smart cities. In this paper, we present …
a vital role in the transformation of traditional cities into smart cities. In this paper, we present …
Astute Segmentation and Classification of leucocytes in blood microscopic smear images using titivated K-means clustering and robust SVM techniques
The microscopic smear images of blood are the images obtained through blood tests. So, by
obtaining these images through blood tests, we can be identifying the number of diseases …
obtaining these images through blood tests, we can be identifying the number of diseases …
An ensemble classification of exudates in color fundus images using an evolutionary algorithm based optimal features selection
Atomic recognition of the Exudates (EXs), the major symbol of diabetic retinopathy is
essential for automated retinal images analysis. In this article, we proposed a novel machine …
essential for automated retinal images analysis. In this article, we proposed a novel machine …
Plasmodium life cycle stage classification based quantification of malaria parasitaemia in thin blood smears
Visual inspection for the quantification of malaria parasitaemiain (MP) and classification of
life cycle stage are hard and time taking. Even though, automated techniques for the …
life cycle stage are hard and time taking. Even though, automated techniques for the …
Plasmodium species aware based quantification of malaria parasitemia in light microscopy thin blood smear
Malaria is a serious worldwide disease, caused by a bite of a female Anopheles mosquito.
The parasite transferred into complex life round in which it is grown and reproduces into the …
The parasite transferred into complex life round in which it is grown and reproduces into the …