Literature DB >> 32735452

Utilizing Artificial Intelligence for Head and Neck Cancer Outcomes Prediction From Imaging.

Tricia Chinnery1, Andrew Arifin2, Keng Yeow Tay3, Andrew Leung3, Anthony C Nichols4, David A Palma2, Sarah A Mattonen1,2, Pencilla Lang2.   

Abstract

Artificial intelligence (AI)-based models have become a growing area of interest in predictive medicine and have the potential to aid physician decision-making to improve patient outcomes. Imaging and radiomics play an increasingly important role in these models. This review summarizes recent developments in the field of radiomics for AI in head and neck cancer. Prediction models for oncologic outcomes, treatment toxicity, and pathological findings have all been created. Exploratory studies are promising; however, validation studies that demonstrate consistency, reproducibility, and prognostic impact remain uncommon. Prospective clinical trials with standardized procedures are required for clinical translation.

Entities:  

Keywords:  artificial intelligence; head and neck cancer; machine learning; predictive modeling; radiomics

Year:  2020        PMID: 32735452     DOI: 10.1177/0846537120942134

Source DB:  PubMed          Journal:  Can Assoc Radiol J        ISSN: 0846-5371            Impact factor:   2.248


  2 in total

1.  Progression Free Survival Prediction for Head and Neck Cancer Using Deep Learning Based on Clinical and PET/CT Imaging Data.

Authors:  Mohamed A Naser; Kareem A Wahid; Abdallah S R Mohamed; Moamen Abobakr Abdelaal; Renjie He; Cem Dede; Lisanne V van Dijk; Clifton D Fuller
Journal:  Head Neck Tumor Segm Chall (2021)       Date:  2022-03-13

2.  Mapping intellectual structures and research hotspots in the application of artificial intelligence in cancer: A bibliometric analysis.

Authors:  Peng-Fei Lyu; Yu Wang; Qing-Xiang Meng; Ping-Ming Fan; Ke Ma; Sha Xiao; Xun-Chen Cao; Guang-Xun Lin; Si-Yuan Dong
Journal:  Front Oncol       Date:  2022-09-22       Impact factor: 5.738

  2 in total

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