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Parasites

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Detection of Peripheral Malarial Parasites in Blood Smears Using Deep Learning Models.

Computational intelligence and neuroscience
Due to the plasmodium parasite, malaria is transmitted mostly through red blood cells. Manually counting blood cells is extremely time consuming and tedious. In a recommendation for the advanced technology stage and analysis of malarial disease, the ...

Classification for avian malaria parasite Plasmodium gallinaceum blood stages by using deep convolutional neural networks.

Scientific reports
The infection of an avian malaria parasite (Plasmodium gallinaceum) in domestic chickens presents a major threat to the poultry industry because it causes economic loss in both the quality and quantity of meat and egg production. Computer-aided diagn...

Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm.

Parasites & vectors
BACKGROUND: Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, their accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST s...

A comparative analysis of deep learning architectures on high variation malaria parasite classification dataset.

Tissue & cell
Malaria, one of the leading causes of death in underdeveloped countries, is primarily diagnosed using microscopy. Computer-aided diagnosis of malaria is a challenging task owing to the fine-grained variability in the appearance of some uninfected and...

Evaluation of alarm notification of artificial intelligence in automated analyzer detection of parasites.

Medicine
To evaluate the alarm notification of artificial intelligence in detecting parasites on the KU-F40 Fully Automatic Feces Analyzer and provide a reference for clinical diagnosis in parasite diseases. A total of 1030 fecal specimens from patients in ou...

[Establishment and application of an artificial intelligence-assisted platform for detection of parasite eggs].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control
OBJECTIVE: To establish an artificial intelligence (AI)-assisted platform for detection of parasite eggs, and to evaluate its detection efficiency and accuracy, so as to provide technical supports for elimination of parasitic diseases.

Multi-stage malaria parasite recognition by deep learning.

GigaScience
MOTIVATION: Malaria, a mosquito-borne infectious disease affecting humans and other animals, is widespread in tropical and subtropical regions. Microscopy is the most common method for diagnosing the malaria parasite from stained blood smear samples....

Complex Network Study of the Immune Epitope Database for Parasitic Organisms.

Current topics in medicinal chemistry
BACKGROUND: Complex network approach allows the representation and analysis of complex systems of interacting agents in an ordered and effective manner, thus increasing the probability of discovering significant properties of them. In the present stu...