Abstract:
"The stage at which lung cancer is diagnosed is a critical factor in assessing its global impact on mortality rates. Early
diagnosis significantly enhances the prognosis.
This article reviews advancements in early lung cancer detection, focusing on imaging technologies, molecular diagnostics, and artificial intelligence (AI). Despite the difficulties presented by the absence of symptoms in the early stages, early detection of lung cancer is crucial for improving treatment outcomes.
Non-invasive methods for detecting cancer biomarkers include low-dose computed tomography (LDCT) and molecular diagnostics. AI identifies subtle patterns indicative of cancer, thereby improving diagnostic accuracy.
This study evaluates the effectiveness, precision, and practicality of these diagnostic methodologies, with an emphasis on recent technological advancements. The findings underscore the pivotal role of early diagnosis in enhancing survival rates and quality of life for lung cancer patients. Early detection offers transformative potential, bringing hope to those affected by this disease.
Furthermore, the research demonstrates how emerging diagnostic tools can bridge the gap between late and early-stage detection, providing new hope for patients. The evolving nature of these tools highlights the importance of early detection in reducing lung cancer prevalence. These advancements herald a promising future for lung cancer management, with the potential to significantly reduce mortality rates and improve patient outcomes globally. Progress in diagnostic technologies represents a transformative leap in the fight against lung cancer.
These innovations aim to bridge the gap between late and early-stage detection, setting the stage for a revolution in patient care. As a result, survival rates and quality of life for lung cancer patients worldwide are expected to see unprecedented improvements."
