Artificial intelligence (AI) in oncology is advancing beyond algorithm development to integration into clinical practice. This review describes the current state of the field, with a specific focus on clinical integration. AI applications are structured according to cancer type and clinical domain, focusing on the four most common cancers and tasks of detection, diagnosis, and treatment. These applications encompass various data modalities, including imaging, genomics, and medical records. We conclude with a summary of existing challenges, evolving solutions, and potential future directions for the field. Significance: AI is increasingly being applied to all aspects of oncology, where several applications are maturing beyond research and development to direct clinical integration. This review summarizes the current state of the field through the lens of clinical translation along the clinical care continuum. Emerging areas are also highlighted, along with common challenges, evolving solutions, and potential future directions for the field.

中文翻译：

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肿瘤学中的人工智能：现状、挑战和未来方向

肿瘤学领域的人工智能 (AI) 正在超越算法开发，逐步融入临床实践。这篇综述描述了该领域的现状，特别关注临床整合。人工智能应用程序根据癌症类型和临床领域进行构建，重点关注四种最常见的癌症以及检测、诊断和治疗任务。这些应用程序涵盖各种数据模式，包括成像、基因组学和医疗记录。最后，我们总结了该领域现有的挑战、不断发展的解决方案以及潜在的未来方向。意义：人工智能越来越多地应用于肿瘤学的各个方面，其中一些应用正在成熟，从研究和开发到直接临床整合。这篇综述从临床护理连续体的临床转化角度总结了该领域的现状。还强调了新兴领域，以及该领域的共同挑战、不断发展的解决方案和潜在的未来方向。