Artificial intelligence (AI) and big data in cancer and precision oncology.
AI, Artificial Intelligence
Artificial intelligence
Big datasets
CNV, Copy Number Variations
Deep learning
Diagnosis
Digital pathology
FFPE, Formalin-Fixed Paraffin-Embedded
LYNA, LYmph Node Assistant
ML, Machine Learning
Machine learning
Medical imaging
NGS and bioinformatics
NGS, Next Generation Sequencing
Precision oncology
Prognosis and drug discovery
TCGA, The Cancer Genome Atlas
Treatment
WSI, Whole Slide Imaging
Journal
Computational and structural biotechnology journal
ISSN: 2001-0370
Titre abrégé: Comput Struct Biotechnol J
Pays: Netherlands
ID NLM: 101585369
Informations de publication
Date de publication:
2020
2020
Historique:
received:
03
07
2020
revised:
21
08
2020
accepted:
21
08
2020
entrez:
30
9
2020
pubmed:
1
10
2020
medline:
1
10
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 32994889
doi: 10.1016/j.csbj.2020.08.019
pii: S2001-0370(20)30372-X
pmc: PMC7490765
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
2300-2311Informations de copyright
© 2020 The Author(s).
Déclaration de conflit d'intérêts
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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