The use of artificial intelligence (AI) is significantly changing the domains of precision oncology and cancer research. AI has made it possible to find hidden patterns in a variety of data sources, such as pathology, genetic profiling, and medical imaging, among others. It has also made it possible to integrate -omics data to provide a more thorough understanding of cancer. AI has also accelerated the creation of new assays for prognostication, cancer characterization, and therapy response prediction. These developments in customizing treatment to a patient's particular cancer features represent a major advancement. Translating these new technologies from research settings to clinical practice presents obstacles, despite AI's great promise.

The primary goal of this special issue is to share the latest findings and developments in all areas of AI in cancer research. With the ultimate goal of enhancing patient care, it also provides professional ideas on how to accelerate AI tools from the lab to the clinic. We invite contributions that examine innovative developments at the nexus of precision oncology, cancer biology, and artificial intelligence, with particular interest in biomarker identification, patient stratification, therapeutic response prediction, AI-assisted cancer genomics, and obstacles in clinical translation.

Through this special issue, we aim to promote cutting-edge computational techniques that improve patient stratification, accelerate the conversion of biological insights into clinically useful strategies, and improve mechanistic understanding in order to advance the integration of artificial intelligence into precision oncology and cancer biology. We welcome researchers from various disciplines to provide interdisciplinary perspectives on all areas of AI in cancer research. Your contributions will play a crucial role in advancing knowledge in this field.

Types of articles welcomed: Original research articles, review articles, case studies, etc.