Artificial Intelligence: Deciphering the Promising New Way to Detect Early Signs of Lung Cancer

Abstract

Artificial intelligence (AI) is transforming lung cancer diagnosis by combining computed tomography imaging technology with AI apps. However, images like chest X-rays and CT scans may miss small tumors or those still in their early stages, leading to false positives and unnecessary tests. AI can improve early detection by making it easier to get tests, finding biomarkers, lowering diagnostic errors, personalizing screening, integrating data, making healthcare more accessible, and constantly changing. AI's ability to find biomarkers and merge multimodal data, including imaging, pathology, and electronic health records, allows for more accurate diagnostic tests and better treatment choices. AI has become a crucial field in clinical areas, particularly in imaging analysis, histopathology evaluation, and genomic assessment of lung cancers. AI is transforming research on lung cancer and therapy, particularly in the identification of promising biomarkers. AI systems have proven their capacity to improve diagnostic precision by minimizing the likelihood of erroneous outcomes, enabling radiologists to make better choices and reduce the incidence of diagnostic errors. AI technologies are crucial for the precise interpretation of genomic markers critical for early detection, accurate diagnosis, and personalized therapy options. Healthcare professionals can employ AI algorithms to develop personalized treatment regimens that correspond with a patient's distinct genetic profile, ensuring medications target the molecular characteristics of their malignancy.