Predicting overall survival in anaplastic thyroid cancer using machine learning approaches.

Arnavaz Hajizadeh BarfejaniMohammadreza RostamiMohammad RahimiHossein Sabori FarShahab GholizadehMorteza BehjatAidin Tarokhian

Published in: European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery (2024)

ML algorithms can accurately predict short-term survival in ATC patients. These models can potentially guide clinical decision-making and individualized treatment strategies.

Keyphrases

end stage renal disease
decision making
ejection fraction
chronic kidney disease
machine learning
prognostic factors
free survival
deep learning
patient reported