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Development of machine learning model algorithm for prediction of 5‐year soft tissue myxoid liposarcoma survival
Author(s) -
Kamalapathy Pramod N.,
Ramkumar Dipak B.,
Karhade Aditya V.,
Kelly Sean,
Raskin Kevin,
Schwab Joseph,
LozanoCalderón Santiago
Publication year - 2021
Publication title -
journal of surgical oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.201
H-Index - 111
eISSN - 1096-9098
pISSN - 0022-4790
DOI - 10.1002/jso.26398
Subject(s) - medicine , logistic regression , machine learning , liposarcoma , artificial intelligence , lasso (programming language) , surveillance, epidemiology, and end results , proportional hazards model , database , myxoid liposarcoma , soft tissue sarcoma , cohort , epidemiology , algorithm , soft tissue , sarcoma , computer science , surgery , pathology , cancer registry , world wide web
Predicting survival in myxoid liposarcoma (MLS) patients is very challenging given its propensity to metastasize and the controversial role of adjuvant therapy. The purpose of this study was to develop a machine-learning algorithm for the prediction of survival at five years for patients with MLS and externally validate it using our institutional cohort.