人工智能（AI）在医疗保健领域中扮演着至关重要的角色，可以用于应对多种致命疾病，如皮肤癌、乳腺癌和肺癌。AI是一种先进的技术形式，它使用基于数学的算法原理，类似于人类思维来认知医疗单位所面临的复杂挑战。癌症是一种多因素病因的疾病，包括许多遗传和表观遗传突变。癌症作为一种复杂疾病，在早期阶段很难被诊断出来。因此，通过人工智能和机器学习（ML）可以及时识别遗传变异和其他主导因素。AI是挖掘药物靶点、其作用机制以及药物与生物体相互作用的协同方法，从大量原始数据中进行数据挖掘。这种协同方法在数据挖掘方面面临着一些挑战，但来自不同科学社区的计算算法对于多靶点药物发现在AI药物靶点发现方面有很大帮助，有助于克服AI在药物靶点发现方面的瓶颈。人工智能和机器学习在不久的将来可能成为医学界的中心，用于疾病的诊断、治疗和评估。在这个综述中，我们探讨了人工智能和机器学习在生物科学中与癌症研究结合的巨大潜力。我们的目标是阐明人工智能和机器学习在癌症研究中的应用，从诊断到个体化治疗等方面。我们强调了人工智能在支持肿瘤学家和其他医疗专业人员做出明智决策、改善患者结果方面的前景角色，通过研究人工智能和癌症控制的交叉点。尽管基于人工智能的医疗治疗表现出巨大的潜力，但在其在临床实践中实施之前必须克服许多挑战。我们对当前阻碍进行了批判性评估，并对基于人工智能的方法未来的方向提供了见解，旨在为强化癌症干预和改善患者护理铺平道路。版权所有 © 2023 Elsevier Ltd.

Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases, such as skin, breast, and lung cancer. AI is an advanced form of technology that uses mathematical-based algorithmic principles similar to those of the human mind for cognizing complex challenges of the healthcare unit. Cancer is a lethal disease with many etiologies, including numerous genetic and epigenetic mutations. Cancer being a multifactorial disease is difficult to be diagnosed at an early stage. Therefore, genetic variations and other leading factors could be identified in due time through AI and machine learning (ML). AI is the synergetic approach for mining the drug targets, their mechanism of action, and drug-organism interaction from massive raw data. This synergetic approach is also facing several challenges in data mining but computational algorithms from different scientific communities for multi-target drug discovery are highly helpful to overcome the bottlenecks in AI for drug-target discovery. AI and ML could be the epicenter in the medical world for the diagnosis, treatment, and evaluation of almost any disease in the near future. In this comprehensive review, we explore the immense potential of AI and ML when integrated with the biological sciences, specifically in the context of cancer research. Our goal is to illuminate the many ways in which AI and ML are being applied to the study of cancer, from diagnosis to individualized treatment. We highlight the prospective role of AI in supporting oncologists and other medical professionals in making informed decisions and improving patient outcomes by examining the intersection of AI and cancer control. Although AI-based medical therapies show great potential, many challenges must be overcome before they can be implemented in clinical practice. We critically assess the current hurdles and provide insights into the future directions of AI-driven approaches, aiming to pave the way for enhanced cancer interventions and improved patient care.Copyright © 2023. Published by Elsevier Ltd.