[HTML][HTML] Image analysis and machine learning for detecting malaria
Malaria remains a major burden on global health, with roughly 200 million cases worldwide
and more than 400,000 deaths per year. Besides biomedical research and political efforts …
and more than 400,000 deaths per year. Besides biomedical research and political efforts …
Deep learning with microfluidics for biotechnology
Advances in high-throughput and multiplexed microfluidics have rewarded biotechnology
researchers with vast amounts of data but not necessarily the ability to analyze complex data …
researchers with vast amounts of data but not necessarily the ability to analyze complex data …
Pneumonia detection using CNN based feature extraction
Pneumonia is a life-threatening infectious disease affecting one or both lungs in humans
commonly caused by bacteria called Streptococcus pneumoniae. One in three deaths in …
commonly caused by bacteria called Streptococcus pneumoniae. One in three deaths in …
[HTML][HTML] Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images
Malaria is a blood disease caused by the Plasmodium parasites transmitted through the bite
of female Anopheles mosquito. Microscopists commonly examine thick and thin blood …
of female Anopheles mosquito. Microscopists commonly examine thick and thin blood …
Deep learning based automatic malaria parasite detection from blood smear and its smartphone based application
Malaria is a life-threatening disease that is spread by the Plasmodium parasites. It is
detected by trained microscopists who analyze microscopic blood smear images. Modern …
detected by trained microscopists who analyze microscopic blood smear images. Modern …
Leveraging deep learning techniques for malaria parasite detection using mobile application
Malaria is a contagious disease that affects millions of lives every year. Traditional diagnosis
of malaria in laboratory requires an experienced person and careful inspection to …
of malaria in laboratory requires an experienced person and careful inspection to …
Evaluations of deep convolutional neural networks for automatic identification of malaria infected cells
This paper studied automatic identification of malaria infected cells using deep learning
methods. We used whole slide images of thin blood stains to compile an dataset of malaria …
methods. We used whole slide images of thin blood stains to compile an dataset of malaria …
Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images
Background Malaria is a life-threatening disease caused by Plasmodium parasites that
infect the red blood cells (RBCs). Manual identification and counting of parasitized cells in …
infect the red blood cells (RBCs). Manual identification and counting of parasitized cells in …
Deep malaria parasite detection in thin blood smear microscopic images
Malaria is a disease activated by a type of microscopic parasite transmitted from infected
female mosquito bites to humans. Malaria is a fatal disease that is endemic in many regions …
female mosquito bites to humans. Malaria is a fatal disease that is endemic in many regions …
Malaria parasite detection from peripheral blood smear images using deep belief networks
D Bibin, MS Nair, P Punitha - IEEE Access, 2017 - ieeexplore.ieee.org
In this paper, we propose a novel method to identify the presence of malaria parasites in
human peripheral blood smear images using a deep belief network (DBN). This paper …
human peripheral blood smear images using a deep belief network (DBN). This paper …