After 18 months of research, this tool has demonstrated over 90% accuracy in identifying early-stage lung cancer.

While the diagnostic accuracy reached 92% in initial tests, researchers acknowledge that the small sample size of 50 lung cancer patients and 50 healthy individuals presents a limitation.

Researchers at Ankara University have developed an innovative AI application designed for the early detection of lung cancer through the analysis of speech.

Participants in the study were asked to read a standardized two-minute speech, allowing the AI to analyze their voice recordings.

The AI processes these voice recordings made in natural environments, utilizing advanced signal processing techniques to detect subtle changes.

By analyzing structural changes in the voice, the application can identify alterations in lung anatomy and function that may indicate cancer.

This method is intended to be low-cost and non-invasive, significantly reducing the reliance on harmful imaging procedures such as x-rays.

The researchers anticipate that the application could be integrated into lung cancer screening programs within two to three years, depending on data collection and legal approvals.

Future studies are planned to gather thousands of recordings to enhance the application's accuracy and reduce error margins.

Assoc. Prof. Dr. Bülent Mustafa Yenigün emphasizes the critical importance of early detection for effective lung cancer treatment.

Led by Assoc. Prof. Dr. Haydar Ankışhan, this project aims to provide a more timely diagnosis of lung cancer compared to current methods.