Dlamini Zodwa, Francies Flavia Zita, Hull Rodney, Marima Rahaba
SAMRC/UP Precision Prevention & Novel Drug Targets for HIV-Associated Cancers (PPNDTHAC) Extramural Unit, Pan African Cancer Research Institute (PACRI), University of Pretoria, Faculty of Health Sciences, Hatfield 0028, South Africa.
Comput Struct Biotechnol J. 2020 Aug 28;18:2300-2311. doi: 10.1016/j.csbj.2020.08.019. eCollection 2020.
Artificial intelligence (AI) and machine learning have significantly influenced many facets of the healthcare sector. Advancement in technology has paved the way for analysis of big datasets in a cost- and time-effective manner. Clinical oncology and research are reaping the benefits of AI. The burden of cancer is a global phenomenon. Efforts to reduce mortality rates requires early diagnosis for effective therapeutic interventions. However, metastatic and recurrent cancers evolve and acquire drug resistance. It is imperative to detect novel biomarkers that induce drug resistance and identify therapeutic targets to enhance treatment regimes. The introduction of the next generation sequencing (NGS) platforms address these demands, has revolutionised the future of precision oncology. NGS offers several clinical applications that are important for risk predictor, early detection of disease, diagnosis by sequencing and medical imaging, accurate prognosis, biomarker identification and identification of therapeutic targets for novel drug discovery. NGS generates large datasets that demand specialised bioinformatics resources to analyse the data that is relevant and clinically significant. Through these applications of AI, cancer diagnostics and prognostic prediction are enhanced with NGS and medical imaging that delivers high resolution images. Regardless of the improvements in technology, AI has some challenges and limitations, and the clinical application of NGS remains to be validated. By continuing to enhance the progression of innovation and technology, the future of AI and precision oncology show great promise.
人工智能(AI)和机器学习对医疗保健领域的许多方面都产生了重大影响。技术进步为以经济高效的方式分析大型数据集铺平了道路。临床肿瘤学和研究正在从人工智能中获益。癌症负担是一个全球现象。降低死亡率的努力需要早期诊断以进行有效的治疗干预。然而,转移性和复发性癌症会不断演变并产生耐药性。检测诱导耐药性的新型生物标志物并确定治疗靶点以加强治疗方案势在必行。新一代测序(NGS)平台的引入满足了这些需求,彻底改变了精准肿瘤学的未来。NGS提供了多种临床应用,这些应用对于风险预测、疾病早期检测、测序和医学成像诊断、准确预后、生物标志物识别以及新药研发治疗靶点的识别都很重要。NGS生成的大型数据集需要专门的生物信息学资源来分析相关且具有临床意义的数据。通过人工智能的这些应用,利用NGS和提供高分辨率图像的医学成像可增强癌症诊断和预后预测。尽管技术有所进步,但人工智能仍存在一些挑战和局限性,NGS的临床应用仍有待验证。通过持续推动创新和技术进步,人工智能和精准肿瘤学的未来前景广阔。