Seixas et al. has achieved over 90% diagnostic accuracy for tuberculosis diagnosis in adult patients by using an artificial neural networks model containing Human Immunodeficiency Virus positivity and pleural effusion laboratory results (smear, culture, adenosine deaminase, serology, and nucleic acid amplification tests). The gene discussed is ADA; the disease is tuberculosis.