Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Pakistan.
Comput Biol Med. 2023 Oct;165:107356. doi: 10.1016/j.compbiomed.2023.107356. Epub 2023 Aug 14.
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.
人工智能（AI）在医疗保健中起着至关重要的作用，可以对抗许多致命疾病，如皮肤癌、乳腺癌和肺癌。AI 是一种先进的技术形式，它使用类似于人类思维的基于数学的算法原理，用于认知医疗单位的复杂挑战。癌症是一种具有许多病因的致命疾病，包括许多遗传和表观遗传突变。由于癌症是一种多因素疾病，因此很难在早期阶段进行诊断。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要因素。AI 是从大量原始数据中挖掘药物靶点、作用机制和药物-生物体相互作用的协同方法。这种协同方法在数据挖掘中也面临着许多挑战，但来自不同科学领域的计算算法对于多靶标药物发现非常有帮助，可以克服 AI 在药物靶标发现方面的瓶颈。在不久的将来，AI 和 ML 可能成为医学领域的核心，用于诊断、治疗和评估几乎任何疾病。在这篇全面的综述中，我们探讨了 AI 和 ML 与生物科学相结合时的巨大潜力，特别是在癌症研究方面。我们的目标是阐明 AI 和 ML 在癌症研究中的许多应用方法，从诊断到个体化治疗。我们通过检查 AI 和癌症控制的交叉点，强调 AI 在支持肿瘤学家和其他医疗专业人员做出明智决策和改善患者结果方面的预期作用。虽然基于 AI 的医学疗法显示出巨大的潜力，但在将其应用于临床实践之前，必须克服许多挑战。我们批判性地评估当前的障碍，并提供对未来 AI 驱动方法的方向的洞察，旨在为增强的癌症干预和改善的患者护理铺平道路。
