Artificial intelligence in lung cancer: current applications, future perspectives, and challenges

Area of Science:

• Oncology
• Medical Informatics
• Bioinformatics

Background:

• Artificial intelligence (AI) is increasingly integrated into oncology.
• Lung cancer research and treatment can benefit from advanced AI technologies.

Purpose of the Study:

• To review current and future applications of AI in lung cancer research and treatment.
• To analyze AI's role in precision medicine for lung cancer, from diagnosis to drug discovery.

Main Methods:

• Comprehensive analysis of AI applications across multi-omics data (genomics, transcriptomics, proteomics, etc.).
• Examination of AI in radiomics, pathomics, and clinical data analysis.
• Review of AI's potential in predicting treatment response and survival rates, especially for non-small cell lung cancer (NSCLC).

Main Results:

• AI enhances early lung cancer detection, treatment personalization, and therapeutic innovation.
• AI facilitates precision medicine by analyzing complex datasets for accurate diagnoses and tailored treatment plans.
• AI shows potential in predicting immunotherapy response and survival outcomes in NSCLC.

Conclusions:

• AI is crucial for advancing lung cancer care, offering improved patient outcomes and quality of life.
• Addressing challenges like data quality, interpretability, and ethics is vital for AI implementation.
• Rigorous validation is essential to fully realize AI's transformative potential in combating lung cancer.