AI Article Synopsis

Article Abstract

Recent advancements in computational power, machine learning, and artificial intelligence technology have enabled automated evaluation of medical images to generate quantitative diagnostic and prognostic biomarkers. Such objective biomarkers are readily available and have the potential to improve personalized treatment, precision medicine, and patient selection for clinical trials. In this article, we explore the merits of the most recent addition to the "-omics" concept for the broader field of head and neck cancer - "Radiomics". This review discusses radiomics studies focused on (molecular) characterization, classification, prognostication and treatment guidance for head and neck squamous cell carcinomas (HNSCC). We review the underlying hypothesis, general concept and typical workflow of radiomic analysis, and elaborate on current and future challenges to be addressed before routine clinical application.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7197186PMC
http://dx.doi.org/10.1186/s41199-020-00053-7DOI Listing

Publication Analysis

Top Keywords

head neck
12
prognostication treatment
8
neck squamous
8
squamous cell
8
cell carcinomas
8
applications radiomics
4
radiomics precision
4
precision diagnosis
4
diagnosis prognostication
4
treatment planning
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!