Utilizing Artificial Intelligence for Head and Neck Cancer Outcomes Prediction From Imaging.
Tricia ChinneryAndrew ArifinKeng Yeow TayAndrew LeungAnthony C NicholsDavid A PalmaSarah A MattonenPencilla LangPublished in: Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes (2020)
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.
Keyphrases
- artificial intelligence
- machine learning
- big data
- deep learning
- clinical trial
- high resolution
- decision making
- lymph node metastasis
- primary care
- emergency department
- case control
- rectal cancer
- magnetic resonance imaging
- oxidative stress
- type diabetes
- contrast enhanced
- randomized controlled trial
- risk assessment
- prostate cancer
- radical prostatectomy
- human health
- climate change
- squamous cell carcinoma
- skeletal muscle
- fluorescence imaging
- study protocol
- weight loss
- double blind
- open label
- clinical evaluation