Blood samples of patients infected with a parasitic worm that causes schistosomiasis contain hidden information that marks different stages of the disease. In our recently published research, our team used machine learning to uncover that hidden information and improve early detection and diagnosis of infection.
The parasite that causes schistosomiasis completes its life cycle in two hosts – first in snails and then in mammals such as people, dogs, and mice. Freshwater worm eggs enter human hosts through the skin and circulate throughout the body, damaging multiple organs, including the liver, intestine, bladder, and urethra. When these larvae reach blood vessels connecting the intestines to the liver, they mature into adult worms. They then release eggs that are excreted when the infected person defecates, continuing the transmission cycle.
Since diagnosis currently relies on detecting eggs in feces, doctors usually miss the early stages of infection. By the time eggs are ...
