Introduction: Cancer remains one of the leading causes of death worldwide, and early detection, accurate diagnosis, and personalized treatment are essential for improving patient outcomes. Artificial intelligence (AI) has emerged as a transformative tool in oncology, offering unprecedented capabilities in the analysis of medical data, diagnosis, and treatment planning. The aim of this paper is to explore the applications of Artificial Intelligence (AI) in cancer diagnosis and treatment, focusing on its impact on early detection, personalized treatment plans, and drug development.
Methods: This paper conducts a comprehensive review of current literature and research on AI applications in oncology, specifically in the areas of medical imaging, genomic data analysis, and clinical decision-making. Various AI techniques such as machine learning, deep learning, and natural language processing are examined for their use in cancer diagnosis and treatment.
Results: AI has shown significant potential in detecting early-stage cancers with high accuracy, particularly in medical imaging, including CT scans, MRIs, and mammograms. It has also played a crucial role in personalized treatment, assisting oncologists in designing tailored therapies based on patient data. AI is also accelerating the drug discovery process by predicting effective compounds for cancer therapy.
Conclusion: Artificial Intelligence is transforming the field of oncology by enhancing diagnostic accuracy, improving treatment personalization, and accelerating drug development. However, challenges such as data quality, privacy concerns, and regulatory approval must be addressed for AI's full potential to be realized in cancer care.