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Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review
Malaria is an infectious disease caused by parasites of the genus Plasmodium spp. It is
transmitted to humans by the bite of an infected female Anopheles mosquito. It is the most …
transmitted to humans by the bite of an infected female Anopheles mosquito. It is the most …
Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases
S Marletta, V L'Imperio, A Eccher, P Antonini… - … -Research and Practice, 2023 - Elsevier
Infectious diseases still threaten the global community, especially in resource-limited
countries. An accurate diagnosis is paramount to proper patient and public health …
countries. An accurate diagnosis is paramount to proper patient and public health …
IMNets: Deep learning using an incremental modular network synthesis approach for medical imaging applications
Deep learning approaches play a crucial role in computer-aided diagnosis systems to
support clinical decision-making. However, develo** such automated solutions is …
support clinical decision-making. However, develo** such automated solutions is …
When collaborative federated learning meets blockchain to preserve privacy in healthcare
Data-driven Machine and Deep Learning (ML/DL) is an emerging approach that uses
medical data to build robust and accurate ML/DL models that can improve clinical decisions …
medical data to build robust and accurate ML/DL models that can improve clinical decisions …
A scalable and transferable federated learning system for classifying healthcare sensor data
With the development of Internet of Medical Things, massive healthcare sensor data (HSD)
are transmitted in the Internet, which faces various security problems. Healthcare data are …
are transmitted in the Internet, which faces various security problems. Healthcare data are …
Clustering-based dual deep learning architecture for detecting red blood cells in malaria diagnostic smears
Computer-assisted algorithms have become a mainstay of biomedical applications to
improve accuracy and reproducibility of repetitive tasks like manual segmentation and …
improve accuracy and reproducibility of repetitive tasks like manual segmentation and …
An ensemble-based approach for automated medical diagnosis of malaria using EfficientNet
Abstract Each year, more than 400,000 people die of malaria. Malaria is a mosquito-borne
transmissible infection that affects humans and other animals. According to World Health …
transmissible infection that affects humans and other animals. According to World Health …
[HTML][HTML] Deep learning for microscopic examination of protozoan parasites
The infectious and parasitic diseases represent a major threat to public health and are
among the main causes of morbidity and mortality. The complex and divergent life cycles of …
among the main causes of morbidity and mortality. The complex and divergent life cycles of …
An efficient model of residual based convolutional neural network with Bayesian optimization for the classification of malarial cell images
A Diker - Computers in Biology and Medicine, 2022 - Elsevier
Background Malaria is a disease caused by the Plasmodium parasite, which results in
millions of deaths in the human population worldwide each year. It is therefore considered a …
millions of deaths in the human population worldwide each year. It is therefore considered a …
Application of machine and deep learning algorithms in optical microscopic detection of Plasmodium: A malaria diagnostic tool for the future
Abstract Machine and deep learning techniques are prevalent in the medical discipline due
to their high level of accuracy in disease diagnosis. One such disease is malaria caused by …
to their high level of accuracy in disease diagnosis. One such disease is malaria caused by …