Houston, Texas, March 24, 2018 — SemanticMD, a leading deep learning medical imaging company, is pleased to announce on World TB Day a collaboration with Co-Diagnostics, Inc. ("CODX") to provide SemanticMD's AI for tuberculosis (TB) solution for X-ray imaging for early detection of TB.CODX has developed a molecular diagnostic test for TB that is much more affordable and accurate than standard sputum tests. SemanticMD's AI for TB solution powered by deep learning will enable customers to leverage insights from chest X-rays captured in clinics to provide rapid and cost-effective patient referrals and ensure that patients have access to world-class radiological and molecular diagnostic services.
SemanticMD has conducted several successful pilots around the world utilizing their deep learning platform in screening chest X-rays for signs of TB. The anticipated collaboration forms the basis of delivering a medical imaging AI and molecular diagnostic solution for TB screening.
TB caused 1.7 million deaths in 2016, surpassing the number of HIV/AIDS deaths globally. 10.4 million people fell ill with TB that year, mostly from poor and vulnerable communities. Over 95% of TB deaths occur in low and middle income countries. Patients with TB may present with mild or no symptoms early on and many affected people arrive at clinics and pharmacies too late with advanced disease, which is difficult to treat and more likely to cause mortality.
One of the keys to tackling TB is early diagnosis. Sputum culture testing is commonly used but has widely varying levels of sensitivity and frequently misses the disease in its early stages. Molecular testing such as Xpert™ – while highly accurate – is too expensive for many middle and low income countries. Chest X-rays (CXR) play a crucial role in TB diagnosis by frontline physicians since CXRs provide a low-cost, rapid examination even in remote settings. Although CXRs are often not pathognomonic for TB, they offer a high sensitivity method for detecting TB-related abnormalities in the lungs.
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