Dxplain automatically provides choices to help the user input data as specifically as possible. Dxplain knows over 5,000 clinical findings. Diseases can be input by the user as clinical findings, or suggested by Dxplain. For example, in a patient with generalized weakness and flaccidity, Dxplain inferred that there was a muscle disorder present which then was a clinical finding that raised the possibility of a sub-phrenic abscess. Similarly, a disease like AIDS can be a diagnosis, but it also can be a clinical finding that raises the risk of other illnesses.
Relationships describe how clinical findings and diseases are related to one another.
This expresses how important it is for a particular finding to be explained by a disease in the differential diagnosis. Findings like headache or rash need not be explained by the diagnosis, but findings like coma, thrombocytopenia, and hallucinations need to be. Dxplain gives users the option of increasing the importance of findings, to make sure they are weighted more heavily in construction of the differential diagnosis. For example, coronary artery aneurisms, while not frequent in Kawasaki disease, strongly support that diagnosis. Possible diseases in the differential diagnosis are then given numerical scores for how well they fit the entered findings.