International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment

International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment

Background The Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) estimate 90- day and 1-year survival in patients with long-bone metastases undergoing surgical treatment and have demonstrated good discriminatory ability on internal validation. However, the performance of a pre...

Full description

Bibliographic Details
Main Authors: Bongers, M.E.R (Author), Groot, O.Q (Author), Hou, C.-H (Author), Hu, M.-H (Author), Karhade, A.V (Author), Ko, J.-C (Author), Lai, Y.-H (Author), Lee, C.-C (Author), Lin, S.-Y (Author), Lin, W.-H (Author), Schwab, J.H (Author), Tseng, T.-E (Author), Verlaan, J.-J (Author), Yang, J.-J (Author), Yang, R.-S (Author), Yen, H.-K (Author)
Format: Article
Language:English
Published: Lippincott Williams and Wilkins 2022
Subjects:
adult
Adult
aged
Aged
Aged, 80 and over
Bone Neoplasms
bone tumor
Extremities
female
Female
human
Humans
limb
machine learning
Machine Learning
male
Male
middle aged
Middle Aged
mortality
pathology
postoperative period
Postoperative Period
predictive value
Predictive Value of Tests
prognosis
Prognosis
Taiwan
very elderly
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items