An Overview of Revolutionizing Lung Cancer Management with AI: Current Advances and Future Prospects

Worldwide health authorities identify lung tumors as one of the most critical medical concerns because patients often die from the condition and discover it too late. Recent technology breakthroughs have made it possible to come up with innovative methods of improving early detection, accurate diagnosis, and successful treatment methods. Modern computer systems enhance medical image examination which reduces misdiagnosis errors and boosts accurate detection of pulmonary diseases. Genomic research obtained advantages from these developments through lab tests which speed up mutation discovery and create individualized therapeutic plans. The use of automated technology in histopathological analysis now leads to optimized tumor classifications as well as better prognosis evaluations. The execution of treatments becomes more individualized because predictive models predict how patients will react to therapeutic interventions during planning stages. Digital tools used for clinical decision support now simplify patient management by assessing combined biological and clinical information. The research momentum for novel therapeutic choices has increased because it presents promising therapeutic options. Healthcare systems and data consistency together with possible biases remain unresolved issues for future improvement. With the advancement of the multi-dimensional data analysis, the refinement of the diagnostic instruments, and the precision guided treatment, it is expected that the prognosis of the lung cancer will be greatly improved, and the patients will get such medical treatment more efficiently and patient centered.