Vida Diagnostics Inc has received 510(k) clearance from the FDA for enhancements to its LungPrint solution, including automated deep learning-based lung and lobe segmentation algorithms. The addition of deep learning algorithms to Vida's LungPrint solution allows the company to improve the performance of lung imaging analysis and enable a more comprehensive assessment of disease probability and progression. This depth of insight empowers physicians to develop personalized treatment plans that can improve outcomes and quality of life. This most recent FDA approval incorporates Vida's deep-learning algorithms, which improve the automated segmentation of the lung and lobes for greater clinical and diagnostic precision, applying the highest standards of technology to clinical practice. "We're living in the age of personalized medicine, where precision algorithms can be used to optimize outcomes for patients," said Susan Wood, PhD, president and CEO of Vida Diagnostics. "The addition of deep-learning capabilities to our already-proven solution is a critical step towards diagnosing and treating lung disease with anatomical precision based on clinical best practices." According to Wood, the VIDA algorithm learns how to analyze lung scans based on intelligence derived from the extensive and diverse database the company has amassed over more than a decade of clinical work. This results in a substantial improvement in accuracy and establishes a scalable platform that supports greater efficiency. Respiratory AI solutions from VIDA are used to assess the lung characteristics associated with chronic, complex lung disease, such as COVID-19 related lung damage, COPD, interstitial lung disease, emphysema, and asthma. In addition to clinical applications, pharmaceutical companies rely on VIDA's ISO 13485-certified core lab processes to facilitate research on drug therapies for people with these life-changing conditions.