Automating vital parasite practises with pre-determined algorithms facilitates in improving accuracy and validity for future experiments.
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.
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.
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.
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.
Reduce human error and fatigue with machine learning and increase efficiency of current protocols.
With embedded algorithms, complex systems can detect and identify parasites with samples, reducing the need for human intervention.
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.
Battle worldwide challenges with world leading technologies with embedded algorithms to reduce human bias and fatigue.