Department of Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.
Department of Genomic Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.
Biomolecules. 2022 Aug 17;12(8):1133. doi: 10.3390/biom12081133.
To provide precision medicine for better cancer care, researchers must work on clinical patient data, such as electronic medical records, physiological measurements, biochemistry, computerized tomography scans, digital pathology, and the genetic landscape of cancer tissue. To interpret big biodata in cancer genomics, an operational flow based on artificial intelligence (AI) models and medical management platforms with high-performance computing must be set up for precision cancer genomics in clinical practice. To work in the fast-evolving fields of patient care, clinical diagnostics, and therapeutic services, clinicians must understand the fundamentals of the AI tool approach. Therefore, the present article covers the following four themes: (i) computational prediction of pathogenic variants of cancer susceptibility genes; (ii) AI model for mutational analysis; (iii) single-cell genomics and computational biology; (iv) text mining for identifying gene targets in cancer; and (v) the NVIDIA graphics processing units, DRAGEN field programmable gate arrays systems and AI medical cloud platforms in clinical next-generation sequencing laboratories. Based on AI medical platforms and visualization, large amounts of clinical biodata can be rapidly copied and understood using an AI pipeline. The use of innovative AI technologies can deliver more accurate and rapid cancer therapy targets.
为了提供精准医学以改善癌症护理，研究人员必须研究临床患者数据，例如电子病历、生理测量、生物化学、计算机断层扫描、数字病理学以及癌症组织的遗传特征。为了解读癌症基因组学中的大型生物数据，必须在高性能计算的人工智能 (AI) 模型和医疗管理平台上建立基于人工智能的操作流程，以实现临床实践中的精准癌症基因组学。为了在患者护理、临床诊断和治疗服务等快速发展的领域中工作，临床医生必须了解 AI 工具方法的基础知识。因此，本文涵盖了以下四个主题：（i）癌症易感性基因的致病性变异的计算预测；（ii）突变分析的 AI 模型；（iii）单细胞基因组学和计算生物学；（iv）癌症中基因靶点的文本挖掘；以及（v）NVIDIA 图形处理单元、DRAGEN 现场可编程门阵列系统和 AI 医疗云平台在临床下一代测序实验室中的应用。基于 AI 医疗平台和可视化，大量的临床生物数据可以使用 AI 管道快速复制和理解。创新 AI 技术的使用可以提供更准确和快速的癌症治疗靶点。
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