A Step Toward Personalized Surgical Decision Making: Machine Learning Predicts One Versus Numerous Melanoma Lymph Node Metastases Using RNA-Sequencing.
Max O MeneveauRick Daniel VavolizzaAnwaruddin MohammadPankaj KumarJoseph T ManderfieldColleen CallahanKevin T LynchTarek AbbasCraig L SlingluffStefan BekiranovPublished in: Annals of surgery (2022)
Gene expression profiles together with clinical variables can distinguish melanoma metastasis patients with 1 pLN versus >1 pLN. Future models trained using PET/CT imaging, gene expression, and relevant clinical variables may further improve accuracy and may predict patients who can be managed with a targeted LN excision rather than a complete TLND.
Keyphrases
- pet ct
- lymph node
- gene expression
- machine learning
- decision making
- high resolution
- dna methylation
- positron emission tomography
- neoadjuvant chemotherapy
- skin cancer
- artificial intelligence
- computed tomography
- squamous cell carcinoma
- radiation therapy
- resistance training
- cancer therapy
- early stage
- body composition
- basal cell carcinoma
- locally advanced