Artificial intelligence-based approaches for detection and classification of different classes of malaria parasites using microscopic images: a systematic review
Artificial Intelligence has played an essential role in detecting malaria, which aims to reduce
the involvement of any human microscopist in order provide an accurate diagnosis with …
the involvement of any human microscopist in order provide an accurate diagnosis with …
Classification of malaria using object detection models
Malaria poses a global health problem every day, as it affects millions of lives all over the
world. A traditional diagnosis requires the manual inspection of blood smears from the …
world. A traditional diagnosis requires the manual inspection of blood smears from the …
[PDF][PDF] Deep learning-based computer assisted detection techniques for malaria parasite using blood smear images
Malaria remains a significant global health concern, impacting various regions worldwide.
Achieving effective treatment and reducing mortality rates hinges on early and accurate …
Achieving effective treatment and reducing mortality rates hinges on early and accurate …
Malaria classification using convolutional neural network: a review
The Convolutional Neural Networks (CNNs) have been used to classify malaria parasites
from blood smear images automatically and successfully gave a good result, thus enabling …
from blood smear images automatically and successfully gave a good result, thus enabling …
Automated detection of malaria implemented by deep learning in PyTorch
The diagnoses of diseases as widespread as malaria has proven to be tough in rural areas.
This is because of the lack of resources and professionals working in these places. In such …
This is because of the lack of resources and professionals working in these places. In such …
[HTML][HTML] Febrile disease modeling and diagnosis system for optimizing medical decisions in resource-scarce settings
Febrile diseases are highly prevalent in tropical regions due to elevated humidity and high
temperatures. These regions, mainly comprising low-and middle-income countries, often …
temperatures. These regions, mainly comprising low-and middle-income countries, often …
Malaria detection through digital microscopic imaging using Deep Greedy Network with transfer learning
Purpose: In conventional diagnosis, the visual inspection of the malaria parasite
Plasmodium falciparum in infected red blood cells under a microscope, is done manually by …
Plasmodium falciparum in infected red blood cells under a microscope, is done manually by …
Deep learning based approach for malaria detection in blood cell images
Malaria, a life-threatening disease, develops due to the bite of female Anopheles mosquito.
It spreads the plasmodium parasites in human blood, killing hundreds of millions of people …
It spreads the plasmodium parasites in human blood, killing hundreds of millions of people …
[PDF][PDF] A systematic review on automatic detection of plasmodium parasite
Plasmodium parasite is the main cause of malaria which has taken many lives. Some
research works have been conducted to detect the Plasmodium parasite automatically. This …
research works have been conducted to detect the Plasmodium parasite automatically. This …
[HTML][HTML] Automatic detection of Opisthorchis viverrini egg in stool examination using convolutional-based neural networks
T Thanchomnang, N Chaibutr, W Maleewong… - PeerJ, 2024 - peerj.com
Background Human opisthorchiasis is a dangerous infectious chronic disease distributed in
many Asian areas in the water-basins of large rivers, Siberia, and Europe. The gold …
many Asian areas in the water-basins of large rivers, Siberia, and Europe. The gold …