Siemens Healthineers, in collaboration with Qure.ai and the Global Fund to Combat AIDS, Tuberculosis, and Malaria, is spearheading an initiative to expedite the integration of artificial intelligence (AI) in the fight against tuberculosis (TB). This joint effort is dedicated to promoting the utilization of AI and machine learning solutions for the swift detection of pulmonary abnormalities associated with TB through chest X-ray analysis.
The diagnosis of TB and the identification of affected individuals remain formidable obstacles in combating this highly contagious disease. Millions of TB cases go undetected each year, making the incorporation of AI technology a critical step towards creating more efficient and precise tools for early detection. Siemens Healthineers firmly believes that AI is the key to addressing TB, a disease claiming a life every two minutes.
The initial focus of this initiative will be on Indonesia, a country harboring over 9% of the world’s TB cases. Although TB is preventable and treatable, less than half of the infected population in Indonesia receives timely treatment. Siemens Healthineers estimates that untreated TB patients can potentially transmit the bacteria to up to 15 individuals within a year.
In aid of this initiative, Siemens Healthineers and Qure.ai will furnish free licenses for their AI image processing technology and provide training to healthcare practitioners. Furthermore, the Global Fund will allocate $157 million in funding between 2021 and 2023 to support targeted interventions against the TB epidemic in Indonesia.
Qure.ai, headquartered in Mumbai, has made significant strides in utilizing AI for TB diagnosis. Their chest X-ray programs expedite TB diagnoses and enhance case detection. Additionally, AI technology has effectively halved the costs associated with follow-up confirmatory testing, establishing itself as a cost-effective solution.
In September, Qure achieved dual 510(k) clearances from the U.S. Food and Drug Administration (FDA) for chest X-ray software applications. One clearance was granted for assessing heart failure risks, while the other pertained to diagnosing pneumothorax and pleural effusion cases. These clearances underscore the growing recognition of AI’s potential in the field of medicine.
Moreover, a recent research study conducted in Vietnam demonstrated that the integration of AI detection into routine healthcare provider procedures could yield a twofold benefit. Individuals undergoing initial TB screening via chest X-rays could also be concurrently assessed for potentially cancerous lung nodules, followed by referrals for subsequent CT scans to investigate any signs of lung cancer.
