The Present State and Potential Applications of Artificial Intelligence in Cancer Diagnosis and Treatment.

Anuja Mishra, Srishti Sharma, Swaroop Kumar Pandey
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Abstract

An aberrant increase in cancer incidences has demanded extreme attention globally despite advancements in diagnostic and management strategies. The high mortality rate is concerning, and tumour heterogeneity at the genetic, phenotypic, and pathological levels exacerbates the problem. In this context, lack of early diagnostic techniques and therapeutic resistance to drugs, sole awareness among the public, coupled with the unavailability of these modern technologies in developing and low-income countries, negatively impact cancer management. One of the prime necessities of the world today is the enhancement of early detection of cancers. Several independent studies have shown that screening individuals for cancer can improve patient survival but are bogged down by risk classification and major problems in patient selection. Artificial intelligence (AI) has significantly advanced the field of oncology, addressing various medical challenges, particularly in cancer management. Leveraging extensive medical datasets and innovative computational technologies, AI, especially through deep learning (DL), has found applications across multiple facets of oncology research. These applications range from early cancer detection, diagnosis, classification, and grading, molecular characterization of tumours, prediction of patient outcomes and treatment responses, personalized treatment, and novel anti-cancer drug discovery. Over the past decade, AI/ML has emerged as a valuable tool in cancer prognosis, risk assessment, and treatment selection for cancer patients. Several patents have been and are being filed and granted. Some of those inventions were explored and are being explored in clinical settings as well. In this review, we will discuss the current status, recent advancements, clinical trials, challenges, and opportunities associated with AI/ML applications in cancer detection and management. We are optimistic about the potential of AI/ML in improving outcomes for cancer and the need for further research and development in this field.

人工智能在癌症诊断和治疗中的现状及潜在应用。
尽管在诊断和管理策略方面取得了进步,但癌症发病率的异常增加要求全球高度关注。高死亡率令人担忧,而肿瘤在遗传、表型和病理水平上的异质性加剧了这一问题。在这种情况下,缺乏早期诊断技术和对药物的治疗耐药性,公众只有认识,再加上发展中国家和低收入国家无法获得这些现代技术,对癌症管理产生了不利影响。当今世界的主要必需品之一是加强对癌症的早期发现。几项独立的研究表明,对个体进行癌症筛查可以提高患者的存活率,但却因风险分类和患者选择中的主要问题而陷入困境。人工智能(AI)极大地推动了肿瘤学领域的发展,解决了各种医疗挑战,特别是在癌症管理方面。利用广泛的医疗数据集和创新的计算技术,人工智能,特别是通过深度学习(DL),已经在肿瘤学研究的多个方面找到了应用。这些应用包括早期癌症检测、诊断、分类和分级、肿瘤的分子特征、患者预后和治疗反应的预测、个性化治疗和新型抗癌药物的发现。在过去的十年中,人工智能/机器学习已经成为癌症患者预后、风险评估和治疗选择的宝贵工具。一些专利已经和正在申请和授予。其中一些发明已经在临床环境中进行了探索。在这篇综述中,我们将讨论AI/ML在癌症检测和管理中的应用的现状、最新进展、临床试验、挑战和机遇。我们对人工智能/机器学习在改善癌症治疗结果方面的潜力以及在这一领域进一步研究和发展的必要性持乐观态度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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