Promising Artificial Technology Being Developed for Lung Cancer Detection

While it may seem intimidating or confusing, artificial intelligence is playing a critical role in the advancement of lung cancer detection and treatment for patients like you. As technology advances, the medical field continues to improve and create better outcomes for those affected by lung cancer.

AI algorithms can analyze medical images to detect abnormalities in the lungs as well as identify early signs of lung cancer, such as lung nodules. Since artificial intelligence can quickly and consistently analyze many images, it reduces the risk of human error. New AI technology continually advances, and lung cancer doctors apply it to medical practices. Working alongside AI, doctors can provide better treatment and identify cancer risks before they do irreparable damage.

Sybil, an emerging technology being developed for early lung cancer detection, is one of the newest artificial intelligence tools. Researchers in Boston have been training and testing this major advancement in early lung cancer screening and hope to eventually use it to assist the public. Sybil is an AI that can identify a patient’s risk of developing lung cancer within six years, making it an invaluable tool for lung cancer screening and early detection. Sybil’s ability to detect pixels that cannot be seen by the human eye in lung scans makes it an asset in early cancer detection.

In one study, the technology accurately predicted whether a person would develop lung cancer in the next year 86-94% of the time. Sybil is just one of the latest steps in strides artificial intelligence is making towards better benefiting the healthcare system. Keep reading to learn about the history and application of AI technology, how it can assist with cancer diagnosis and treatment, and the potential benefits to patients and doctors alike!

History of Artificial Intelligence and Lung Cancer

The history of using artificial intelligence for diagnosing and treating cancer is marked by significant technological advancements throughout the decades — the roots of healthcare-based AI trace back to the early development of AI concepts in the 1950s. Researchers then explored the potential of computers to assist with the analysis of medical data and decision-making processes such as lung cancer detection. Since then, the use of artificial intelligence in diagnosis and lung cancer treatment has advanced and expanded.

In the 1970s, AI systems used rules to diagnose diseases and forms of cancer. In the 1990s, AI applications for cancer diagnosis began to focus on image analysis and pattern recognition for detection. Medical professionals use artificial intelligence to identify tumors and assess their characteristics. More recently, AI has played an instrumental role in the discovery of drugs for cancer treatment. Furthermore, these systems can develop personalized treatment plans for a patient based on their genetic, clinical, and imaging data.

AI technology in healthcare has inspired some criticism and concerns regarding data security and patient privacy. As health records are important and valuable information, hackers often target them. Access to an individual’s medical records can enable hackers to commit crimes, blackmail patients, or use the data in exploitative ways. Healthcare professionals are combatting this threat by de-identifying the data before uploading it into an AI system, which means they do not attach any patient name to the record. Another is to enforce due diligence and enhanced compliance monitoring when it comes to the collection and transportation of medical records. Maintaining the confidentiality and security of artificial intelligence data is crucial to building a better healthcare system.

How Does Artificial Intelligence Detect Lung Cancer?

AI algorithms prove incredibly useful at detecting lung cancer. Human eyes are at risk for error, and artificial intelligence can detect patterns and pixels that eyes cannot. They can analyze medical images like X-rays, CT scans, and MRIs to identify abnormalities or patterns in the lungs. Artificial intelligence can also help reduce the number of false positives in lung cancer screening by improving the accuracy of nodule detection. Furthermore, AI can assess a patient’s risk of developing lung cancer by considering factors such as a patient’s smoking history, medical history, and exposure to environmental risks. AI can also assist with continuous monitoring. Technology can track changes in nodule sizes and characteristics over time, enabling doctors to make informed decisions about treatment or follow-ups. This is one example of how technology and medical professionals can work together to improve the healthcare industry and provide better care to patients.

In trials thus far, artificial intelligence has proved incredibly accurate with lung cancer detection. In one research study, an AI system had a 97% accuracy rate when diagnosing two common types of lung cancer by analyzing tissue sample slides. However, it can be hard to guarantee that the real-world application of AI will accurately reflect the outcomes of trials. There is no doubt, though, that as technology advances, AI innovation will continue to affect the healthcare industry, especially regarding cancer.

Sybil Approval Process Timeline

Sybil, a promising new artificial intelligence tool that focuses on predicting an individual’s future cancer risk, has not yet been approved by the FDA. If it is, it could play a valuable role in lung cancer detection and diagnosis. Announced at the beginning of 2023, Sybil represents an encouraging advancement for early detection technology. Early lung cancer detection means that the long-term prognosis outcome becomes significantly better. Sybil only has to analyze one lung scan to predict the risk of developing cancer in an individual.

So far, Sybil has only worked with scans of patients who have smoked in the past. The next step in the research and testing of the AI is to see if the technology can identify lung cancer in individuals who have not smoked or are undergoing smoking cessation. Each advancement and improvement that Sybil makes is hopefully one step closer to getting the Food and Drug Administration’s approval for artificial intelligence and to helping more patients.

Approved Early Detection Methods

Approved early detection methods for lung cancer feature a combination of traditional and artificial intelligence-related approaches. Early detection aims to identify lung cancer at an earlier stage, where it is more treatable. Medical professionals widely accept low-dose computed tomography (LDCT) traditional screening methods to identify lung cancer. It uses X-ray technology to acquire detailed images of an individual’s lungs using lower radiation than a standard CT scan does. Healthcare professionals recommend LDCT for patients who may be at high risk of developing lung cancer, including current or former heavy smokers, as it helps detect lung nodules and tumors at an earlier stage.

Artificial intelligence is prevalent in many approved early-detection methods for lung cancer diagnosis. Computer-aided diagnosis (CAD) systems use AI algorithms to assist radiologists in interpreting medical images, like CT scans. Additionally, radiomics utilizes AI to gather quantitative data from medical images, including texture, shape, and intensity features of potential tumors or nodules. Artificial intelligence can also be used to develop predictive models that assess a patient’s risk of developing lung cancer. The models created consider various factors to provide personalized risk assessments that can contribute to an effective treatment plan. While AI-related methods hold promise for early lung cancer detection, healthcare professionals typically use them alongside traditional approaches as they continue to improve. There is a promising future for AI and lung cancer, and hope that as technology improves, so will the detection and treatment of this disease that affects so many.

Lung Cancer Resources

Early detection of cancer, especially lung cancer, is vital when considering the best possible treatment and outcome for a diagnosed patient. If you or a loved one think you may be at risk for lung cancer, there are resources available! Our Lung Cancer Center Team is here to assist you every step of the way, from connecting you to medical help to providing support and legal help. We are dedicated to providing you with the most up-to-date and relevant information regarding lung cancer, including information about artificial intelligence, clinical trials, and treatment options. Don’t hesitate to contact our team and let us help you navigate this difficult time in your life.