In many new things, there has been a groundbreaking new tool developed by the scientists of Ankara University (AU) in Turkey. This tool promises to detect lung cancer in its early stages. The best part? The tool uses nothing more than just your voice. This AI-powered application is used to analyze speech patterns in order to identify structural changes caused by the diseases. This is a great way of testing, as it is non-invasive in nature, thus is a low-cost method of screening for such a deadly disease. Detecting Through SpeechThe project is being led by Associate Professor Dr Haydar Ankishan of AU's Stem Cell Institute. The idea centered to the research was: changes in a person's voice could reflect anatomical or functional disruption in the lungs, especially those caused by cancer. “In our study, we considered the structure of the voice, the anatomical structure of the lungs, and the circulatory system,” Ankışhan said at a press conference held at AU’s Ibn-i Sina Hospital. “We proposed that the voice could provide information about lung cancer.”The study took a span of 18 months, with the team being able to develop a system that can detect stage-one lung cancer with an accuracy rate exceeding 90%. How Does This Work?The technology is able to capture a person's voice in a natural environment. Then the voice is processed using advanced signal analysis techniques and machine learning. The AI model is trained on these audio samples to differentiate between healthy individuals and those with early-stage lung cancer. Faculty member of AU's Faculty of Medicine, who is also a key contributor in the study, Dr Bülent Mustafa Yenigün emphasized the importance of such early detection. “The later lung cancer is diagnosed, the harder it becomes to treat. We aimed for a method that’s non-invasive, low-cost, and doesn’t expose patients to harmful radiation,” he explained.If one has to understand the science behind it, then one must understand what the AI listens for. The science behind this method is actually rooted in how tumors affect airflow and resonance in the lungs. As masses form, they can disrupt the natural vibrations and frequencies that are part of normal speech. Thus, the AI is trained to detect these variations, regardless of how subtle they may be. Many of these variations, in fact, may not be noticeable to the human ear. “Our application identifies deviations in frequency and sound resonance that can indicate a pathological mass in the lungs,” Yenigün explained.Is It Accessible?The researchers are optimistic about the future. If legal approvals are secured and larger datasets are collected, they estimate that the technology could be integrated into standard lung cancer screening programs within two to three years. In a best-case scenario, it could be available in as little as one to two years.If successful, this voice-based screening tool could become a revolutionary step in early cancer detection—accessible, painless, and potentially life-saving.What Is Lung Cancer?As per the NHS UK, Lung Cancer is one of the most common and serious types of cancer, which has affected more than 43,000 people in UK, annually. In many cases there are no symptoms, however, you must look out for these: a persistent coughcoughing up bloodpersistent breathlessnessunexplained tiredness and weight lossan ache or pain when breathing or coughingWhen cancer begins in the lungs, it is referred to as primary lung cancer. In contrast, if cancer originates elsewhere in the body and spreads to the lungs, it is known as secondary lung cancer. This explanation focuses specifically on primary lung cancer.Primary lung cancer is broadly categorized based on the type of cells where the cancer develops. The two main types are:Non-small-cell lung cancer (NSCLC): This is the most common form, making up about 80–85% of all cases. NSCLC includes three subtypes:Squamous cell carcinomaAdenocarcinomaLarge-cell carcinomaSmall-cell lung cancer (SCLC): Less common than NSCLC, this type tends to grow and spread more quickly.Understanding the type of lung cancer is essential for determining the appropriate treatment approach.