Parasite burden analysis and motility indexing are vital steps within parasite research to advance our current knowledge and understanding. Machine Learning and artificial intelligence can facilitate in overcoming current worldwide challenged including rising drug resistance. With image classification technology with embedded algorithms, these process’ of faecal egg counting and motility indexing will speed up and simplify current methods, ultimately improving accuracy and validity.

Accurate and Valid

Automating vital parasite practises with pre-determined algorithms facilitates in improving accuracy and validity for future experiments.

Endless Research Opportunities:

Automated parasite motility indexing, and faecal egg counting can be applied to numerous real-world problems and facilitate in not only speeding up but also enhancing the investigation powers.

Speed

Real-world parasite challenges do not wait. Automation of normally time-consuming methods will speed up diagnosis and drug discovery pipelines, ultimately increasing health and performance.

Improved Health

With artificial intelligence, we can analyse parasite samples at speeds beyond human abilities, decreasing diagnosis and treatment time frames and ultimately improving animal and human health.

Drug Discovery

Machine learning can facilitate in current drug discovery techniques, speeding up the process with analytics beyond human scale to assist in current challenges facing parasite disease.

Applied AI:

Reduce human error and fatigue with machine learning and increase efficiency of current protocols.

Image and Video Classification

With embedded algorithms, complex systems can detect and identify parasites with samples, reducing the need for human intervention.

Transmission Insights

Mode of transmissions are still a novelty to our knowledge for new emerging parasites. Prediction models with applied intelligence can assist in feature extraction and enhance current investigation methods.

Anthelmintic Resistance:

Battle worldwide challenges with world leading technologies with embedded algorithms to reduce human bias and fatigue.

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