LAIA
Cervical cancer ranks 2nd in deaths of women worldwide. Rural areas are the most prone to suffer from this disease because, in these communities has found the largest number of cases in advanced stage. The main factors that lead to a late diagnosis is the response time for a study and the number of specialists that there are, since it does not cover the demand that the studies require. Our solution is the development of an artificial intelligence algorithm called LAIA that detects cervical cancer lesions. LAIA complements the Pap Smear.
In a first stage, we receive images from the Pap smear. Then LAIA performs the processing to detect cervical cancer injuries and sends the result to the specialist to make the diagnosis with priority of the abnormal results. Our value proposal is to decrease the response time of the Pap Smear and increase the number of studies performed by a laboratory