AI Medical Compendium Journal:
Parasites & vectors

Showing 11 to 20 of 20 articles

AI-driven convolutional neural networks for accurate identification of yellow fever vectors.

Parasites & vectors
BACKGROUND: Identifying mosquito vectors is crucial for controlling diseases. Automated identification studies using the convolutional neural network (CNN) have been conducted for some urban mosquito vectors but not yet for sylvatic mosquito vectors ...

Double vision: 2D and 3D mosquito trajectories can be as valuable for behaviour analysis via machine learning.

Parasites & vectors
BACKGROUND: Mosquitoes are carriers of tropical diseases, thus demanding a comprehensive understanding of their behaviour to devise effective disease control strategies. In this article we show that machine learning can provide a performance assessme...

An optimised YOLOv4 deep learning model for efficient malarial cell detection in thin blood smear images.

Parasites & vectors
BACKGROUND: Malaria is a serious public health concern worldwide. Early and accurate diagnosis is essential for controlling the disease's spread and avoiding severe health complications. Manual examination of blood smear samples by skilled technician...

Implementing deep learning models for the classification of Echinococcus multilocularis infection in human liver tissue.

Parasites & vectors
BACKGROUND: The histological diagnosis of alveolar echinococcosis can be challenging. Decision support models based on deep learning (DL) are increasingly used to aid pathologists, but data on the histology of tissue-invasive parasitic infections are...

Identification of parameters and formulation of a statistical and machine learning model to identify Babesia canis infections in dogs using available ADVIA hematology analyzer data.

Parasites & vectors
BACKGROUND: Canine babesiosis is an important tick-borne disease in endemic regions. One of the relevant subspecies in Europe is Babesia canis, and it can cause severe clinical signs such as hemolytic anemia. Apart from acute clinical symptoms dogs c...

Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso.

Parasites & vectors
BACKGROUND: Improving the knowledge and understanding of the environmental determinants of malaria vector abundance at fine spatiotemporal scales is essential to design locally tailored vector control intervention. This work is aimed at exploring the...

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...

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

Parasites & vectors
BACKGROUND: Fecal examination is an important component of routine companion animal wellness exams. Sensitivity and specificity of fecal examinations, however, are influenced by sample preparation methodologies and the level of training and experienc...

Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning.

Parasites & vectors
BACKGROUND: Culicoides biting midges transmit viruses resulting in disease in ruminants and equids such as bluetongue, Schmallenberg disease and African horse sickness. In the past decades, these diseases have led to important economic losses for far...

2-methyl butyramide, a previously identified urine biomarker for Ascaris lumbricoides, is not present in infected Indonesian individuals.

Parasites & vectors
UNLABELLED: ᅟ: Previous reports suggest that the 2-methyl butyramide and 2-methyl valeramide metabolites of Ascaris lumbricoides in urine of infected individuals could be considered as urinary biomarkers for active infection. We have developed an LC-...