Lyme disease is a life-threatening illness that is most commonly transmitted by ticks. In the United States alone, the CDC estimates that there are approximately 476,000 cases of Lyme disease per year—a number that has grown roughly 160% in recent years—with more than 1 in 2 ticks carrying Lyme disease in certain areas. 

The problem also isn’t just the rate of infection. The true issue lies in the nature of the disease, and how the world hasn’t been able to formally recognize the danger of Lyme disease. For instance, Californian case numbers have grown by 195% from 2015 to 2017— yet, during the same time period, most California hospitals refused to offer antibiotics for Lyme disease.

The longer it takes to treat Lyme disease, the more severe the issue becomes. In fact, if not treated in a timely manner, 10 to 20 percent of patients continue to experience symptoms for months and even years after receiving treatment. The difficulty of diagnosis also adds to the problem. Not only do typical symptoms mimic those of more conventional illnesses like the common cold or the flu, but blood testing for Lyme is only accurate “29 to 40 percent of the time.”  All of these factors cause most doctors to shy away from dealing out Lyme disease diagnoses.

A common preventative measure includes removing embedded ticks before they have the chance to engorge into one’s skin. But this act, known as “tick checking,” isn’t foolproof. The sizes of ticks can range drastically, making them hard to identify. 

In order to increase the performance of tick checks, scientists have leveraged the integration of artificial intelligence in order to more 

accurately detect ticks. Several research papers on this topic have proposed phone applications that use the smartphone’s camera as an input for the AI to output a prediction on.